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Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas.
L. R. Medsker and L. Jain, “Recurrent neural networks,” Design and Applications
2001
Earlier work this paper cites.
Cambridge university press, 2005
D. Tse and P. Viswanath, Fundamentals of wireless communication · 2005
Earlier work this paper cites.
B. van Arem, C. J. G. van Driel, and R. Visser, “The impact of cooperative adaptive cruise control on traffic-flow characteristics,” IEEE Transactions on Intelligent Transportation Systems
2006
Earlier work this paper cites.
CRC press, 2006
J. Shi, Stream of variation modeling and analysis for multistage manufacturing processes · 2006
Earlier work this paper cites.
S.-K. Kim, J.-H. Jeon, C.-H. Cho, J.-B. Ahn, and S.-H. Kwon, “Dynamic modeling and control of a grid-connected hybrid generation system with versatile power transfer,” IEEE transactions on industrial electronics
2008
Earlier work this paper cites.
Cambridge university press, 2009
J. Pearl, Causality · 2009
Earlier work this paper cites.
Wiley New York, 2009
D. C. Montgomery, Statistical quality control · 2009
Earlier work this paper cites.
V. Chandola, A. Banerjee, and V. Kumar, “Anomaly detection: A survey,” ACM computing surveys (CSUR)
2009
Earlier work this paper cites.
J. A. Halderman, S. D. Schoen, N. Heninger, W. Clarkson, W. Paul, J. A. Calandrino, A. J. Feldman, J. Appelbaum, and E. W. Felten, “Lest we remember: cold-boot attacks on encryption keys,” Communications of the ACM
2009
Earlier work this paper cites.
L. Atzori, A. Iera, and G. Morabito, “The internet of things: A survey,” Computer networks
2010
Earlier work this paper cites.
I. Boticki and H.-J. So, “Quiet captures: A tool for capturing the evidence of seamless learning with mobile devices,” in Proceedings of the 9th International Conference of the Learning Sciences-Volume 1
2010
Earlier work this paper cites.
Q. Yang, J. A. Barria, and T. C. Green, “Communication infrastructures for distributed control of power distribution networks,” IEEE Transactions on Industrial Informatics
2011
Earlier work this paper cites.
C. Reinisch, M. Kofler, F. Iglesias, and W. Kastner, “Thinkhome energy efficiency in future smart homes,” EURASIP Journal on Embedded Systems
2011
Earlier work this paper cites.
D. Philipp, F. Durr, and K. Rothermel, “A sensor network abstraction for flexible public sensing systems,” in 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems
2011
Earlier work this paper cites.
S. Adams, I. Arel, J. Bach, R. Coop, R. Furlan, B. Goertzel, J. S. Hall, A. Samsonovich, M. Scheutz, M. Schlesinger, et al
2012
Earlier work this paper cites.
A. Sehgal, V. Perelman, S. Kuryla, and J. Schonwalder, “Management of resource constrained devices in the internet of things,” IEEE Communications Magazine
2012
Earlier work this paper cites.
N. El-Bendary, M. M. M. Fouad, R. A. Ramadan, S. Banerjee, and A. E. Hassanien, “Smart environmental monitoring using wireless sensor networks,” K15146_C025. indd
2013
Earlier work this paper cites.
D. P. Kingma and M. Welling, “Auto-encoding variational Bayes,” arXiv preprint arXiv:1312.6114
2013
Earlier work this paper cites.
K. Muandet, D. Balduzzi, and B. Schölkopf, “Domain generalization via invariant feature representation,” in International conference on machine learning
2013
Earlier work this paper cites.
A. Ben-Tal, D. Den Hertog, A. De Waegenaere, B. Melenberg, and G. Rennen, “Robust solutions of optimization problems affected by uncertain probabilities,” Management Science
2013
Earlier work this paper cites.
F. A. Bender, M. Kaszynski, and O. Sawodny, “Drive cycle prediction and energy management optimization for hybrid hydraulic vehicles,” IEEE Transactions on Vehicular Technology
2013
Earlier work this paper cites.
A. Asadi and V. Mancuso, “A survey on opportunistic scheduling in wireless communications,” IEEE Communications surveys & tutorials
2013
Earlier work this paper cites.
M. Abu-Elkheir, M. Hayajneh, and N. A. Ali, “Data management for the internet of things: Design primitives and solution,” Sensors
2013
Earlier work this paper cites.
B. Goertzel, “Artificial general intelligence: concept, state of the art, and future prospects,” Journal of Artificial General Intelligence
2014
Earlier work this paper cites.
S. Kumar and S. R. Lee, “Android based smart home system with control via bluetooth and internet connectivity,” in The 18th IEEE International Symposium on Consumer Electronics (ISCE 2014)
2014
Earlier work this paper cites.
A. Vadiee and V. Martin, “Energy management strategies for commercial greenhouses,” Applied Energy
2014
Earlier work this paper cites.
Advances in Computing and Communications and their Impact on Transportation Science and Technologies
M. A. Mohd Zulkefli, J. Zheng, Z. Sun, and H. X. Liu, “Hybrid powertrain optimization with trajectory prediction based on inter-vehicle-communication and vehicle-infrastructure-integration,” Transportation Research Part C: Emerging Technologies · 2014
Earlier work this paper cites.
H. Lasi, P. Fettke, H.-G. Kemper, T. Feld, and M. Hoffmann, “Industry 4.0,” Business & information systems engineering
2014
Earlier work this paper cites.
M. M. Rodgers, V. M. Pai, and R. S. Conroy, “Recent advances in wearable sensors for health monitoring,” IEEE Sensors Journal
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
S. Shafieezadeh Abadeh, P. M. Mohajerin Esfahani, and D. Kuhn, “Distributionally robust logistic regression,” Advances in Neural Information Processing Systems
2015
Earlier work this paper cites.
Y. Zhang, R. Padman, and N. Patel, “Paving the cowpath: Learning and visualizing clinical pathways from electronic health record data,” Journal of biomedical informatics
2015
Earlier work this paper cites.
S. E. Shladover, C. Nowakowski, X.-Y. Lu, and R. Ferlis, “Cooperative adaptive cruise control: Definitions and operating concepts,” Transportation Research Record
2015
Earlier work this paper cites.
Q. Huang, J. Zhang, A. Sabbaghi, and T. Dasgupta, “Optimal offline compensation of shape shrinkage for three-dimensional printing processes,” Iie transactions
2015
Earlier work this paper cites.
R. Jin and X. Deng, “Ensemble modeling for data fusion in manufacturing process scale-up,” IIE Transactions
2015
Earlier work this paper cites.
B. P. Woolf, “Ai and education: Celebrating 30 years of marriage.,” in AIED Workshops
2015
Earlier work this paper cites.
N. D. Lane, S. Bhattacharya, P. Georgiev, C. Forlivesi, and F. Kawsar, “An early resource characterization of deep learning on wearables, smartphones and internet-of-things devices,” in Proceedings of the 2015 international workshop on internet of things towards applications
2015
Earlier work this paper cites.
S. Han, J. Pool, J. Tran, and W. Dally, “Learning both weights and connections for efficient neural network,” in Advances in Neural Information Processing Systems
2015
Earlier work this paper cites.
M. Courbariaux, Y. Bengio, and J.-P. David, “Binaryconnect: Training deep neural networks with binary weights during propagations,” in Advances in neural information processing systems
2015
Earlier work this paper cites.
S. Kraijak and P. Tuwanut, “A survey on iot architectures, protocols, applications, security, privacy, real-world implementation and future trends,” in 11th international conference on wireless communications, networking and mobile computing (WiCOM 2015)
2015
Earlier work this paper cites.
Y.-M. Fang and C.-C. Chang, “Users’ psychological perception and perceived readability of wearable devices for elderly people,” Behaviour & Information Technology
2016
Earlier work this paper cites.
J. Peters, P. Bühlmann, and N. Meinshausen, “Causal inference by using invariant prediction: identification and confidence intervals,” Journal of the Royal Statistical Society. Series B (Statistical Methodology)
2016
Earlier work this paper cites.
S. Erfani, M. Baktashmotlagh, M. Moshtaghi, X. Nguyen, C. Leckie, J. Bailey, and R. Kotagiri, “Robust domain generalisation by enforcing distribution invariance,” in Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16)
2016
Earlier work this paper cites.
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. Lempitsky, “Domain-adversarial training of neural networks,” The journal of machine learning research
2016
Earlier work this paper cites.
S. S. I. Samuel, “A review of connectivity challenges in iot-smart home,” in 2016 3rd MEC International conference on big data and smart city (ICBDSC)
2016
Earlier work this paper cites.
S. Pradeep, T. Kousalya, K. A. Suresh, and J. Edwin, “Iot and its connectivity challenges in smart home,” Int. Res. J. Eng. Technol
2016
Earlier work this paper cites.
A. S. Miner, A. Milstein, S. Schueller, R. Hegde, C. Mangurian, and E. Linos, “Smartphone-based conversational agents and responses to questions about mental health, interpersonal violence, and physical health,” JAMA internal medicine
2016
Earlier work this paper cites.
N. Gaur and B. P. Mohanty, “Land-surface controls on near-surface soil moisture dynamics: Traversing remote sensing footprints,” Water Resources Research
2016
Earlier work this paper cites.
J. Hu, Y. Shao, Z. Sun, M. Wang, J. Bared, and P. Huang, “Integrated optimal eco-driving on rolling terrain for hybrid electric vehicle with vehicle-infrastructure communication,” Transportation Research Part C: Emerging Technologies
2016
Earlier work this paper cites.
Springer Link, 2016
S. Onori, L. Serrao, and G. Rizzoni, Hybrid Electric Vehicles Energy Management Strategies · 2016
Earlier work this paper cites.
F. Wang, M. A. M. Zulkefli, Z. Sun, and K. A. Stelson, “Energy management strategy for a power-split hydraulic hybrid wheel loader,” Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
2016
Earlier work this paper cites.
J. P. F. Trovão, M.-A. Roux, É. Ménard, and M. R. Dubois, “Energy-and power-split management of dual energy storage system for a three-wheel electric vehicle,” IEEE Transactions on Vehicular Technology
2016
Earlier work this paper cites.
I. A. Ntousakis, I. K. Nikolos, and M. Papageorgiou, “Optimal vehicle trajectory planning in the context of cooperative merging on highways,” Transportation Research Part C: Emerging Technologies
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
H. Sun, X. Deng, K. Wang, and R. Jin, “Logistic regression for crystal growth process modeling through hierarchical nonnegative garrote-based variable selection,” Iie Transactions
2016
Earlier work this paper cites.
C. R. Gómez Rodríguez and E. G. Barrantes S, “Using differential privacy for the internet of things,” Privacy and Identity Management. Facing up to Next Steps: 11th IFIP WG 9.2, 9.5, 9.6/11.7, 11.4, 11.6/SIG 9.2. 2 International Summer School, Karlstad, Sweden, August 21-26, 2016, Revised Selected Papers 11
2016
Earlier work this paper cites.
S. Bhattacharya and N. D. Lane, “From smart to deep: Robust activity recognition on smartwatches using deep learning,” in 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)
2016
Earlier work this paper cites.
Y. Guo, A. Yao, and Y. Chen, “Dynamic network surgery for efficient dnns,” in Advances In Neural Information Processing Systems
2016
Earlier work this paper cites.
W. Wen, C. Wu, Y. Wang, Y. Chen, and H. Li, “Learning structured sparsity in deep neural networks,” in Advances in Neural Information Processing Systems
2016
Earlier work this paper cites.
D. Lin, S. Talathi, and S. Annapureddy, “Fixed point quantization of deep convolutional networks,” in International Conference on Machine Learning
2016
Earlier work this paper cites.
J. Wu, C. Leng, Y. Wang, Q. Hu, and J. Cheng, “Quantized convolutional neural networks for mobile devices,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
2016
Earlier work this paper cites.
M. Rastegari, V. Ordonez, J. Redmon, and A. Farhadi, “Xnor-net: Imagenet classification using binary convolutional neural networks,” in European Conference on Computer Vision
2016
Earlier work this paper cites.
I. Hubara, M. Courbariaux, D. Soudry, R. El-Yaniv, and Y. Bengio, “Binarized neural networks,” in Advances in neural information processing systems
2016
Earlier work this paper cites.
N. D. Lane, S. Bhattacharya, P. Georgiev, C. Forlivesi, L. Jiao, L. Qendro, and F. Kawsar, “Deepx: A software accelerator for low-power deep learning inference on mobile devices,” in Proceedings of the 15th International Conference on Information Processing in Sensor Networks
2016
Earlier work this paper cites.
S. Han, H. Shen, M. Philipose, S. Agarwal, A. Wolman, and A. Krishnamurthy, “Mcdnn: An approximation-based execution framework for deep stream processing under resource constraints,” in Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services
2016
Earlier work this paper cites.
M. Ahmed, A. N. Mahmood, and J. Hu, “A survey of network anomaly detection techniques,” Journal of Network and Computer Applications
2016
Earlier work this paper cites.
F. Tramèr, F. Zhang, A. Juels, M. K. Reiter, and T. Ristenpart, “Stealing machine learning models via prediction apis.,” in USENIX security symposium
2016
Earlier work this paper cites.
L. Farhan, S. T. Shukur, A. E. Alissa, M. Alrweg, U. Raza, and R. Kharel, “A survey on the challenges and opportunities of the internet of things (iot),” in 2017 Eleventh International Conference on Sensing Technology (ICST)
2017
Earlier work this paper cites.
A. Kanawaday and A. Sane, “Machine learning for predictive maintenance of industrial machines using iot sensor data,” in 2017 8th IEEE international conference on software engineering and service science (ICSESS)
2017
Earlier work this paper cites.
P. J. Rani, J. Bakthakumar, B. P. Kumaar, U. P. Kumaar, and S. Kumar, “Voice controlled home automation system using natural language processing (nlp) and internet of things (iot),” in 2017 Third International Conference on Science Technology Engineering & Management (ICONSTEM)
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” Advances in neural information processing systems
2017
Earlier work this paper cites.
M. Marjani, F. Nasaruddin, A. Gani, A. Karim, I. A. T. Hashem, A. Siddiqa, and I. Yaqoob, “Big iot data analytics: architecture, opportunities, and open research challenges,” ieee access
2017
Earlier work this paper cites.
S. Motiian, M. Piccirilli, D. A. Adjeroh, and G. Doretto, “Unified deep supervised domain adaptation and generalization,” in Proceedings of the IEEE international conference on computer vision
2017
Earlier work this paper cites.
C. Finn, P. Abbeel, and S. Levine, “Model-agnostic meta-learning for fast adaptation of deep networks,” in International conference on machine learning
2017
Earlier work this paper cites.
H. Namkoong and J. C. Duchi, “Variance-based regularization with convex objectives,” Advances in neural information processing systems
2017
Earlier work this paper cites.
L. K. A. Terashmila, T. Iqbal, and G. Mann, “A comparison of low cost wireless communication methods for remote control of grid-tied converters,” in 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE)
2017
Earlier work this paper cites.
T. K. Hui, R. S. Sherratt, and D. D. Sánchez, “Major requirements for building smart homes in smart cities based on internet of things technologies,” Future Generation Computer Systems
2017
Earlier work this paper cites.
M. S. Hossain, M. A. Rahman, and G. Muhammad, “Cyber–physical cloud-oriented multi-sensory smart home framework for elderly people: An energy efficiency perspective,” Journal of Parallel and Distributed Computing
2017
Earlier work this paper cites.
C. Z. Yue and S. Ping, “Voice activated smart home design and implementation,” in 2017 2nd International Conference on Frontiers of Sensors Technologies (ICFST)
2017
Earlier work this paper cites.
S. Michie, L. Yardley, R. West, K. Patrick, and F. Greaves, “Developing and evaluating digital interventions to promote behavior change in health and health care: Recommendations resulting from an international workshop,” J Med Internet Res
2017
Earlier work this paper cites.
Y. Shao, M. A. Mohd Zulkefli, and Z. Sun, “Vehicle and Powertrain Optimization for Autonomous and Connected Vehicles,” Mechanical Engineering
2017
Earlier work this paper cites.
B. Beak, K. L. Head, and Y. Feng, “Adaptive coordination based on connected vehicle technology,” Transportation Research Record
2017
Earlier work this paper cites.
Y. Shao and Z. Sun, “Robust eco-cooperative adaptive cruise control with gear shifting,” in 2017 American Control Conference (ACC)
2017
Earlier work this paper cites.
J. Rios-Torres and A. A. Malikopoulos, “Automated and cooperative vehicle merging at highway on-ramps,” IEEE Transactions on Intelligent Transportation Systems
2017
Earlier work this paper cites.
Y. Han, D. Chen, and S. Ahn, “Variable speed limit control at fixed freeway bottlenecks using connected vehicles,” Transportation Research Part B: Methodological
2017
Earlier work this paper cites.
H. Sun, K. Wang, Y. Li, C. Zhang, and R. Jin, “Quality modeling of printed electronics in aerosol jet printing based on microscopic images,” Journal of Manufacturing Science and Engineering
2017
Earlier work this paper cites.
H. Sun, P. K. Rao, Z. J. Kong, X. Deng, and R. Jin, “Functional quantitative and qualitative models for quality modeling in a fused deposition modeling process,” IEEE Transactions on Automation Science and Engineering
2017
Earlier work this paper cites.
U. P. D. Ani, H. He, and A. Tiwari, “Review of cybersecurity issues in industrial critical infrastructure: manufacturing in perspective,” Journal of Cyber Security Technology
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
Y. He, X. Zhang, and J. Sun, “Channel pruning for accelerating very deep neural networks,” in Computer Vision (ICCV), 2017 IEEE International Conference on
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
E. Park, J. Ahn, and S. Yoo, “Weighted-entropy-based quantization for deep neural networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
2017
Earlier work this paper cites.
A. Zhou, A. Yao, Y. Guo, L. Xu, and Y. Chen, “Incremental network quantization: Towards lossless cnns with low-precision weights,” in International Conference on Learning Representations (ICLR)
2017
Earlier work this paper cites.
A. Paszke, S. Gross, S. Chintala, and G. Chanan, “Pytorch,” 2017
2017
Earlier work this paper cites.
L. N. Huynh, Y. Lee, and R. K. Balan, “Deepmon: Mobile gpu-based deep learning framework for continuous vision applications,” in Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services
2017
Earlier work this paper cites.
S. Yao, S. Hu, Y. Zhao, A. Zhang, and T. Abdelzaher, “Deepsense: A unified deep learning framework for time-series mobile sensing data processing,” in Proceedings of the 26th International Conference on World Wide Web
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
T. Wang, C.-K. Wen, H. Wang, F. Gao, T. Jiang, and S. Jin, “Deep learning for wireless physical layer: Opportunities and challenges,” China Communications
2017
Earlier work this paper cites.
D. Nguyen, C. Nguyen, T. Duong-Ba, H. Nguyen, A. Nguyen, and T. Tran, “Joint network coding and machine learning for error-prone wireless broadcast,” in 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC)
2017
Earlier work this paper cites.
U. Pagallo, M. Durante, and S. Monteleone, “What is new with the internet of things in privacy and data protection? four legal challenges on sharing and control in iot,” Data protection and privacy:(In) visibilities and infrastructures
2017
Earlier work this paper cites.
K.-H. N. Bui, J. J. Jung, and D. Camacho, “Consensual negotiation-based decision making for connected appliances in smart home management systems,” Sensors
2018
Earlier work this paper cites.
M. Syafrudin, G. Alfian, N. L. Fitriyani, and J. Rhee, “Performance analysis of iot-based sensor, big data processing, and machine learning model for real-time monitoring system in automotive manufacturing,” Sensors
2018
Earlier work this paper cites.
L. Scime and J. Beuth, “Anomaly detection and classification in a laser powder bed additive manufacturing process using a trained computer vision algorithm,” Additive Manufacturing
2018
Earlier work this paper cites.
M. Rojas-Carulla, B. Schölkopf, R. Turner, and J. Peters, “Invariant models for causal transfer learning,” The Journal of Machine Learning Research
2018
Earlier work this paper cites.
Y. Li, M. Gong, X. Tian, T. Liu, and D. Tao, “Domain generalization via conditional invariant representations,” in Proceedings of the AAAI conference on artificial intelligence
2018
Earlier work this paper cites.
A. Creswell, T. White, V. Dumoulin, K. Arulkumaran, B. Sengupta, and A. A. Bharath, “Generative adversarial networks: An overview,” IEEE signal processing magazine
2018
Earlier work this paper cites.
Y. Li, X. Tian, M. Gong, Y. Liu, T. Liu, K. Zhang, and D. Tao, “Deep domain generalization via conditional invariant adversarial networks,” in Proceedings of the European conference on computer vision (ECCV)
2018
Earlier work this paper cites.
D. Li, Y. Yang, Y.-Z. Song, and T. Hospedales, “Learning to generalize: Meta-learning for domain generalization,” in Proceedings of the AAAI conference on artificial intelligence
2018
Earlier work this paper cites.
R. Volpi, H. Namkoong, O. Sener, J. C. Duchi, V. Murino, and S. Savarese, “Generalizing to unseen domains via adversarial data augmentation,” Advances in neural information processing systems
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
M. A. A. H. Khan, N. Roy, and A. Misra, “Scaling human activity recognition via deep learning-based domain adaptation,” in 2018 IEEE international conference on pervasive computing and communications (PerCom)
2018
Earlier work this paper cites.
J. Wang, V. W. Zheng, Y. Chen, and M. Huang, “Deep transfer learning for cross-domain activity recognition,” in proceedings of the 3rd International Conference on Crowd Science and Engineering
2018
Earlier work this paper cites.
PhD thesis, Memorial University of Newfoundland, 2018
K. A. T. Lasagani, A communication method for remote control of grid-tied converters · 2018
Earlier work this paper cites.
N. F. Roslan, A. Luna, J. Rocabert, J. I. Candela, and P. Rodriguez, “Remote power control injection of grid-connected power converters based on virtual flux,” Energies
2018
Earlier work this paper cites.
S. Balakrishnan, H. Vasudavan, and R. K. Murugesan, “Smart home technologies: A preliminary review,” in Proceedings of the 6th International Conference on Information Technology: IoT and Smart City
2018
Earlier work this paper cites.
H. Singh, V. Pallagani, V. Khandelwal, and U. Venkanna, “Iot based smart home automation system using sensor node,” in 2018 4th International Conference on Recent Advances in Information Technology (RAIT)
2018
Earlier work this paper cites.
A. Radford, K. Narasimhan, T. Salimans, I. Sutskever, et al
2018
Earlier work this paper cites.
A. Rajkomar, E. Oren, K. Chen, A. M. Dai, N. Hajaj, M. Hardt, P. J. Liu, X. Liu, J. Marcus, M. Sun, et al
2018
Earlier work this paper cites.
T. Zebin, M. Sperrin, N. Peek, and A. J. Casson, “Human activity recognition from inertial sensor time-series using batch normalized deep lstm recurrent networks,” in 2018 40th annual international conference of the IEEE engineering in medicine and biology society (EMBC)
2018
Earlier work this paper cites.
L. Quebrajo, M. Perez-Ruiz, L. Pérez-Urrestarazu, G. Martínez, and G. Egea, “Linking thermal imaging and soil remote sensing to enhance irrigation management of sugar beet,” Biosystems Engineering
2018
Earlier work this paper cites.
S. Puengsungwan and K. Jiraserccamomkul, “Iot based stress detection for organic lettuce farms using chlorophyll fluorescence (chf),” in 2018 Global Wireless Summit (GWS)
2018
Earlier work this paper cites.
J. Giraldo, D. Urbina, A. Cardenas, J. Valente, M. Faisal, J. Ruths, N. O. Tippenhauer, H. Sandberg, and R. Candell, “A survey of physics-based attack detection in cyber-physical systems,” ACM Computing Surveys (CSUR)
2018
Earlier work this paper cites.
A. Vahidi and A. Sciarretta, “Energy saving potentials of connected and automated vehicles,” Transportation Research Part C: Emerging Technologies
2018
Earlier work this paper cites.
Z. Qin, Y. Luo, W. Zhuang, Z. Pan, K. Li, and H. Peng, “Simultaneous optimization of topology, control and size for multi-mode hybrid tracked vehicles,” Applied Energy
2018
Earlier work this paper cites.
Z. Wang, G. Wu, P. Hao, and M. J. Barth, “Cluster-wise cooperative eco-approach and departure application for connected and automated vehicles along signalized arterials,” IEEE Transactions on Intelligent Vehicles
2018
Earlier work this paper cites.
Optimal Eco-Approach Control With Traffic Prediction for Connected Vehicles
2018
Earlier work this paper cites.
Z. Wang, G. Wu, and M. J. Barth, “A review on cooperative adaptive cruise control (cacc) systems: Architectures, controls, and applications,” in 2018 21st International Conference on Intelligent Transportation Systems (ITSC)
2018
Earlier work this paper cites.
Y. Feng, J. Zheng, and H. X. Liu, “Real-time detector-free adaptive signal control with low penetration of connected vehicles,” Transportation Research Record
2018
Earlier work this paper cites.
J. Li, R. Jin, and Z. Y. Hang, “Integration of physically-based and data-driven approaches for thermal field prediction in additive manufacturing,” Materials & Design
2018
Earlier work this paper cites.
T. Chen, T. Moreau, Z. Jiang, L. Zheng, E. Yan, H. Shen, M. Cowan, L. Wang, Y. Hu, L. Ceze, et al
2018
Earlier work this paper cites.
M. Xu, M. Zhu, Y. Liu, F. X. Lin, and X. Liu, “Deepcache: Principled cache for mobile deep vision,” in Proceedings of the 24th Annual International Conference on Mobile Computing and Networking
2018
Earlier work this paper cites.
S. Aslam, W. Ejaz, and M. Ibnkahla, “Energy and spectral efficient cognitive radio sensor networks for internet of things,” IEEE Internet of Things Journal
2018
Earlier work this paper cites.
Y. Wei, L. Pan, S. Liu, L. Wu, and X. Meng, “Drl-scheduling: An intelligent qos-aware job scheduling framework for applications in clouds,” IEEE Access
2018
Earlier work this paper cites.
B. Wang and N. Z. Gong, “Stealing hyperparameters in machine learning,” in 2018 IEEE symposium on security and privacy (SP)
2018
Earlier work this paper cites.
L. Cui, C. Xu, S. Yang, J. Z. Huang, J. Li, X. Wang, Z. Ming, and N. Lu, “Joint optimization of energy consumption and latency in mobile edge computing for internet of things,” IEEE Internet of Things Journal
2018
Earlier work this paper cites.
G. Rosner and E. Kenneally, “Clearly opaque: Privacy risks of the internet of things,” in Rosner, Gilad and Kenneally, Erin, Clearly Opaque: Privacy Risks of the Internet of Things (May 1, 2018). IoT Privacy Forum
2018
Earlier work this paper cites.
S. Zheng, N. Apthorpe, M. Chetty, and N. Feamster, “User perceptions of smart home iot privacy,” Proceedings of the ACM on human-computer interaction
2018
Earlier work this paper cites.
S. Wachter, “Normative challenges of identification in the internet of things: Privacy, profiling, discrimination, and the gdpr,” Computer law & security review
2018
Earlier work this paper cites.
J. H. Nord, A. Koohang, and J. Paliszkiewicz, “The internet of things: Review and theoretical framework,” Expert Systems with Applications
2019
Earlier work this paper cites.
J. Pierce, “Smart home security cameras and shifting lines of creepiness: A design-led inquiry,” in Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
2019
Earlier work this paper cites.
K.-H. N. Bui and J. J. Jung, “Aco-based dynamic decision making for connected vehicles in iot system,” IEEE Transactions on Industrial Informatics
2019
Earlier work this paper cites.
J. D. M.-W. C. Kenton and L. K. Toutanova, “Bert: Pre-training of deep bidirectional transformers for language understanding,” in Proceedings of NAACL-HLT
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
L. Wen, L. Gao, and X. Li, “A new deep transfer learning based on sparse auto-encoder for fault diagnosis,” IEEE Transactions on Systems, Man, and Cybernetics: Systems
2019
Earlier work this paper cites.
Y. Zhang and J. Yan, “Domain-adversarial transfer learning for robust intrusion detection in the smart grid,” in 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
2019
Earlier work this paper cites.
Q. Dou, D. Coelho de Castro, K. Kamnitsas, and B. Glocker, “Domain generalization via model-agnostic learning of semantic features,” Advances in Neural Information Processing Systems
2019
Earlier work this paper cites.
Y. Li, Y. Yang, W. Zhou, and T. Hospedales, “Feature-critic networks for heterogeneous domain generalization,” in International Conference on Machine Learning
2019
Earlier work this paper cites.
R. Volpi and V. Murino, “Addressing model vulnerability to distributional shifts over image transformation sets,” in Proceedings of the IEEE/CVF International Conference on Computer Vision
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
S. Sahoo, T. Dragičević, and F. Blaabjerg, “Cyber security in control of grid-tied power electronic converters–challenges and vulnerabilities,” IEEE Journal of Emerging and Selected Topics in Power Electronics
2019
Earlier work this paper cites.
S. Sahoo, S. Mishra, J. C.-H. Peng, and T. Dragičević, “A stealth cyber-attack detection strategy for dc microgrids,” IEEE Transactions on Power Electronics
2019
Earlier work this paper cites.
F. Li, R. Xie, B. Yang, L. Guo, P. Ma, J. Shi, J. Ye, and W. Song, “Detection and identification of cyber and physical attacks on distribution power grids with pvs: An online high-dimensional data-driven approach,” IEEE Journal of Emerging and Selected Topics in Power Electronics
2019
Earlier work this paper cites.
W. A. Jabbar, T. K. Kian, R. M. Ramli, S. N. Zubir, N. S. Zamrizaman, M. Balfaqih, V. Shepelev, and S. Alharbi, “Design and fabrication of smart home with internet of things enabled automation system,” IEEE access
2019
Earlier work this paper cites.
M. Domb, “Smart home systems based on internet of things,” in Internet of Things (IoT) for automated and smart applications
2019
Earlier work this paper cites.
S. K. Vishwakarma, P. Upadhyaya, B. Kumari, and A. K. Mishra, “Smart energy efficient home automation system using iot,” in 2019 4th international conference on internet of things: Smart innovation and usages (IoT-SIU)
2019
Earlier work this paper cites.
A. Yang, C. Zhang, Y. Chen, Y. Zhuansun, and H. Liu, “Security and privacy of smart home systems based on the internet of things and stereo matching algorithms,” IEEE Internet of Things Journal
2019
Earlier work this paper cites.
V. Bianchi, M. Bassoli, G. Lombardo, P. Fornacciari, M. Mordonini, and I. De Munari, “Iot wearable sensor and deep learning: An integrated approach for personalized human activity recognition in a smart home environment,” IEEE Internet of Things Journal
2019
Earlier work this paper cites.
Q. Xie, M. Wang, Y. Zhao, Z. He, Y. Li, G. Wang, and Y. Lian, “A personalized beat-to-beat heart rate detection system from ballistocardiogram for smart home applications,” IEEE transactions on biomedical circuits and systems
2019
Earlier work this paper cites.
M. Talal, A. Zaidan, B. Zaidan, A. S. Albahri, A. H. Alamoodi, O. S. Albahri, M. Alsalem, C. K. Lim, K. L. Tan, W. Shir, et al
2019
Earlier work this paper cites.
Z. Yang, Z. Dai, Y. Yang, J. Carbonell, R. R. Salakhutdinov, and Q. V. Le, “Xlnet: Generalized autoregressive pretraining for language understanding,” Advances in neural information processing systems
2019
Earlier work this paper cites.
M. Guevara and R. Vargas, “Downscaling satellite soil moisture using geomorphometry and machine learning,” PloS One
2019
Earlier work this paper cites.
N. Gaur and B. P. Mohanty, “A nomograph to incorporate geophysical heterogeneity in soil moisture downscaling,” Water Resources Research
2019
Earlier work this paper cites.
X. Feng, F. Yan, and X. Liu, “Study of wireless communication technologies on internet of things for precision agriculture,” Wireless Personal Communications
2019
Earlier work this paper cites.
M. H. Homaei, E. Salwana, and S. Shamshirband, “An enhanced distributed data aggregation method in the internet of things,” Sensors
2019
Earlier work this paper cites.
Q. He, H. Peng, M. Sheng, S. Hu, J. Qiu, and J. Gu, “Humidity control strategies for solid-state fermentation: Capillary water supply by water-retention materials and negative-pressure auto-controlled irrigation,” Frontiers in Bioengineering and Biotechnology
2019
Earlier work this paper cites.
M. Benjamin and S. Yik, “Precision livestock farming in swine welfare: a review for swine practitioners,” Animals
2019
Earlier work this paper cites.
M. Jorquera-Chavez, S. Fuentes, F. R. Dunshea, R. D. Warner, T. Poblete, and E. C. Jongman, “Modelling and validation of computer vision techniques to assess heart rate, eye temperature, ear-base temperature and respiration rate in cattle,” Animals
2019
Earlier work this paper cites.
G. Naik, B. Choudhury, and J.-M. Park, “Ieee 802.11bd & 5g nr v2x: Evolution of radio access technologies for v2x communications,” IEEE Access
2019
Cited alongside, same era.
M. A. M. Zulkefli and Z. Sun, “Fast numerical powertrain optimization strategy for connected hybrid electric vehicles,” IEEE Transactions on Vehicular Technology
2019
Cited alongside, same era.
Optimal Speed Control for a Connected and Autonomous Electric Vehicle Considering Battery Aging and Regenerative Braking Limits
2019
Cited alongside, same era.
L. Xu, J. Lu, B. Ran, F. Yang, and J. Zhang, “Cooperative merging strategy for connected vehicles at highway on-ramps,” Journal of Transportation Engineering, Part A: Systems
2019
Cited alongside, same era.
A. Ghiasi, X. Li, and J. Ma, “A mixed traffic speed harmonization model with connected autonomous vehicles,” Transportation Research Part C: Emerging Technologies
X. Zeng, Y. Zhang, J. Jiao, and K. Yin, “Route-based transit signal priority using connected vehicle technology to promote bus schedule adherence,” IEEE Transactions on Intelligent Transportation Systems
2021
Later among the works it cites.
Q. Yang, S. Fu, H. Wang, and H. Fang, “Machine-learning-enabled cooperative perception for connected autonomous vehicles: Challenges and opportunities,” IEEE Network
2021
Later among the works it cites.
Z. Yang, Y. Feng, and H. X. Liu, “A cooperative driving framework for urban arterials in mixed traffic conditions,” Transportation Research Part C: Emerging Technologies
2021
Later among the works it cites.
A. Prakash, K. Chitta, and A. Geiger, “Multi-modal fusion transformer for end-to-end autonomous driving,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2019
Cited alongside, same era.
A. A. Malikopoulos, S. Hong, B. B. Park, J. Lee, and S. Ryu, “Optimal control for speed harmonization of automated vehicles,” IEEE Transactions on Intelligent Transportation Systems
2019
Cited alongside, same era.
Q. Guo, L. Li, and X. (Jeff) Ban, “Urban traffic signal control with connected and automated vehicles: A survey,” Transportation Research Part C: Emerging Technologies
2019
Cited alongside, same era.
M. A. Abdel-Aty, Q. Cai, N. Eluru, S. Hasan, W. Chung, S. Rahman, Y. Gong, H. Rahman, et al
2019
Cited alongside, same era.
M. Hadi, M. S. Iqbal, T. Wang, Y. Xiao, M. Arafat, S. Afreen, et al
2019
Cited alongside, same era.
B. Xu, X. J. Ban, Y. Bian, W. Li, J. Wang, S. E. Li, and K. Li, “Cooperative method of traffic signal optimization and speed control of connected vehicles at isolated intersections,” IEEE Transactions on Intelligent Transportation Systems
2019
Cited alongside, same era.
B. Lindemann, F. Fesenmayr, N. Jazdi, and M. Weyrich, “Anomaly detection in discrete manufacturing using self-learning approaches,” Procedia CIRP
2019
Cited alongside, same era.
J. Prinsloo, S. Sinha, and B. von Solms, “A review of industry 4.0 manufacturing process security risks,” Applied Sciences
2019
Cited alongside, same era.
T. Zheng, M. Ardolino, A. Bacchetti, and M. Perona, “The applications of industry 4.0 technologies in manufacturing context: a systematic literature review,” International Journal of Production Research
2021
Later among the works it cites.
L. Bu, Y. Zhang, H. Liu, X. Yuan, J. Guo, and S. Han, “An iiot-driven and ai-enabled framework for smart manufacturing system based on three-terminal collaborative platform,” Advanced Engineering Informatics
2021
Later among the works it cites.
L. J. Segura, T. Wang, C. Zhou, and H. Sun, “Online droplet anomaly detection from streaming videos in inkjet printing,” Additive Manufacturing
2021
Later among the works it cites.
S. Hajifar, H. Sun, F. M. Megahed, L. A. Jones-Farmer, E. Rashedi, and L. A. Cavuoto, “A forecasting framework for predicting perceived fatigue: Using time series methods to forecast ratings of perceived exertion with features from wearable sensors,” Applied Ergonomics
2021
Later among the works it cites.
S. Hajifar, S. R. Lamooki, L. A. Cavuoto, F. M. Megahed, and H. Sun, “Investigation of heterogeneity sources for occupational task recognition via transfer learning,” Sensors
2021
Later among the works it cites.
O. Mokgoantle, “Ethics and morality in the fourth industrial revolution: Rethinking ethics, values and innovation in the digital age,” Information Systems Audit and Control Association
2021
Later among the works it cites.
T. T. Huong, T. P. Bac, D. M. Long, T. D. Luong, N. M. Dan, B. D. Thang, K. P. Tran, et al
2021
Later among the works it cites.
X. Wang, S. Garg, H. Lin, J. Hu, G. Kaddoum, M. J. Piran, and M. S. Hossain, “Toward accurate anomaly detection in industrial internet of things using hierarchical federated learning,” IEEE Internet of Things Journal
2021
Later among the works it cites.
X. Jin, P.-Y. Chen, C.-Y. Hsu, C.-M. Yu, and T. Chen, “Cafe: Catastrophic data leakage in vertical federated learning,” Advances in Neural Information Processing Systems
2021
Later among the works it cites.
J. D. Toscano, S. Hajifar, C. O. Segura, L. J. Segura, and H. Sun, “Deformation analysis of 3d printed metacarpophalangeal and interphalangeal joints via transfer learning,” in International Manufacturing Science and Engineering Conference
2021
Later among the works it cites.
S. A. Niaki, E. Haghighat, T. Campbell, A. Poursartip, and R. Vaziri, “Physics-informed neural network for modelling the thermochemical curing process of composite-tool systems during manufacture,” Computer Methods in Applied Mechanics and Engineering
2021
Later among the works it cites.
G. Li, C. Yuan, S. Kamarthi, M. Moghaddam, and X. Jin, “Data science skills and domain knowledge requirements in the manufacturing industry: A gap analysis,” Journal of Manufacturing Systems
2021
Later among the works it cites.
M. A. Canbaz, K. OHearon, M. McKee, and M. N. Hossain, “Iot privacy and security in teaching institutions: Inside the classroom and beyond,” in 2021 ASEE Virtual Annual Conference Content Access
2021
Later among the works it cites.
A. Andiyan, D. Rusmana, Y. Hari, M. Sitorus, Z. Trinova, and M. Surur, “Disruption of iot in adapting online learning during the covid-19 pandemic.,” International Journal of Early Childhood Special Education
2021
Later among the works it cites.
W. Niu, J. Guan, Y. Wang, G. Agrawal, and B. Ren, “Dnnfusion: accelerating deep neural networks execution with advanced operator fusion,” in Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation
2021
Later among the works it cites.
2021
Later among the works it cites.
Y. Cai, H. Li, G. Yuan, W. Niu, Y. Li, X. Tang, B. Ren, and Y. Wang, “Yolobile: Real-time object detection on mobile devices via compression-compilation co-design,” in Proceedings of the AAAI conference on artificial intelligence
2021
Later among the works it cites.
A. Badi and I. Mahgoub, “Reapiot: Reliable, energy-aware network protocol for large-scale internet-of-things (iot) applications,” IEEE Internet of Things Journal
2021
Later among the works it cites.
X. Ma, H. Sun, Q. Wang, and R. Q. Hu, “User scheduling for federated learning through over-the-air computation,” in 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)
2021
Later among the works it cites.
A. B. Nassif, M. A. Talib, Q. Nasir, and F. M. Dakalbab, “Machine learning for anomaly detection: A systematic review,” Ieee Access
2021
Later among the works it cites.
W. Zhou, L. Guan, P. Liu, and Y. Zhang, “Automatic firmware emulation through invalidity-guided knowledge inference,” in 30th USENIX Security Symposium (USENIX Security 21)
2021
Later among the works it cites.
Arm Ltd., “Arm TrustZone Technology.” https://developer.arm.com/ip-products/security-ip/trustzone/
2021
Later among the works it cites.
Hex Five Security, Inc, “The First TEE For RISC-V.” https://hex-five.com/multizone-security-sdk/
2021
Later among the works it cites.
G. Sun, Y. Cong, J. Dong, Q. Wang, L. Lyu, and J. Liu, “Data poisoning attacks on federated machine learning,” IEEE Internet of Things Journal
2021
Later among the works it cites.
N. Carlini, F. Tramer, E. Wallace, M. Jagielski, A. Herbert-Voss, K. Lee, A. Roberts, T. B. Brown, D. Song, U. Erlingsson, et al
2021
Later among the works it cites.
B. Rana and Y. Singh, “Internet of things and uav: An interoperability perspective,” Unmanned Aerial Vehicles for Internet of Things (IoT) Concepts, Techniques, and Applications
2021
Later among the works it cites.
N. L. Kazanskiy, M. A. Butt, and S. N. Khonina, “Recent advances in wearable optical sensor automation powered by battery versus skin-like battery-free devices for personal healthcare—a review,” Nanomaterials
2022
Later among the works it cites.
OpenAI, “Introducing chatgpt,” 2022
2022
Later among the works it cites.
2022
Later among the works it cites.
L. Ouyang, J. Wu, X. Jiang, D. Almeida, C. Wainwright, P. Mishkin, C. Zhang, S. Agarwal, K. Slama, A. Ray, et al
2022
Later among the works it cites.
G. Mai, C. Cundy, K. Choi, Y. Hu, N. Lao, and S. Ermon, “Towards a foundation model for geospatial artificial intelligence (vision paper),” in Proceedings of the 30th International Conference on Advances in Geographic Information Systems
2022
Later among the works it cites.
N. Du, Y. Huang, A. M. Dai, S. Tong, D. Lepikhin, Y. Xu, M. Krikun, Y. Zhou, A. W. Yu, O. Firat, et al
2022
Later among the works it cites.
2022
Later among the works it cites.
2022
Later among the works it cites.
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer, “High-resolution image synthesis with latent diffusion models,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
2022
Later among the works it cites.
2022
Later among the works it cites.
C. Saharia, W. Chan, S. Saxena, L. Li, J. Whang, E. L. Denton, K. Ghasemipour, R. Gontijo Lopes, B. Karagol Ayan, T. Salimans, et al
2022
Later among the works it cites.
C. Saharia, W. Chan, H. Chang, C. Lee, J. Ho, T. Salimans, D. Fleet, and M. Norouzi, “Palette: Image-to-image diffusion models,” in ACM SIGGRAPH 2022 Conference Proceedings
2022
Later among the works it cites.
B. Kawar, M. Elad, S. Ermon, and J. Song, “Denoising diffusion restoration models,” in Advances in Neural Information Processing Systems
2022
Later among the works it cites.
C. Saharia, J. Ho, W. Chan, T. Salimans, D. J. Fleet, and M. Norouzi, “Image super-resolution via iterative refinement,” IEEE Transactions on Pattern Analysis and Machine Intelligence
2022
Later among the works it cites.
N. Fei, Z. Lu, Y. Gao, G. Yang, Y. Huo, J. Wen, H. Lu, R. Song, X. Gao, T. Xiang, et al
2022
Later among the works it cites.
J. Li, D. Li, C. Xiong, and S. Hoi, “BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation,” in International Conference on Machine Learning
2022
Later among the works it cites.
A. Sgueglia, A. Di Sorbo, C. A. Visaggio, and G. Canfora, “A systematic literature review of iot time series anomaly detection solutions,” Future Generation Computer Systems
2022
Later among the works it cites.
X. Yang, L. Chai, R. B. Bist, S. Subedi, and Z. Wu, “A deep learning model for detecting cage-free hens on the litter floor,” Animals
2022
Later among the works it cites.
T. A. Shaikh, W. A. Mir, T. Rasool, and S. Sofi, “Machine learning for smart agriculture and precision farming: towards making the fields talk,” Archives of Computational Methods in Engineering
2022
Later among the works it cites.
M. Al-Rawashdeh, P. Keikhosrokiani, B. Belaton, M. Alawida, and A. Zwiri, “Iot adoption and application for smart healthcare: a systematic review,” Sensors
2022
Later among the works it cites.
Z. Liu, M. He, Z. Jiang, Z. Wu, H. Dai, L. Zhang, S. Luo, T. Han, X. Li, X. Jiang, et al
2022
Later among the works it cites.
J. Wei, X. Wang, D. Schuurmans, M. Bosma, F. Xia, E. Chi, Q. V. Le, D. Zhou, et al
2022
Later among the works it cites.
M.-H. Guo, T.-X. Xu, J.-J. Liu, Z.-N. Liu, P.-T. Jiang, T.-J. Mu, S.-H. Zhang, R. R. Martin, M.-M. Cheng, and S.-M. Hu, “Attention mechanisms in computer vision: A survey,” Computational Visual Media
2022
Later among the works it cites.
B. Dhingra, J. R. Cole, J. M. Eisenschlos, D. Gillick, J. Eisenstein, and W. W. Cohen, “Time-aware language models as temporal knowledge bases,” Transactions of the Association for Computational Linguistics
2022
Later among the works it cites.
K. Zhou, Z. Liu, Y. Qiao, T. Xiang, and C. C. Loy, “Domain generalization: A survey,” IEEE Transactions on Pattern Analysis and Machine Intelligence
2022
Later among the works it cites.
J. Wang, C. Lan, C. Liu, Y. Ouyang, T. Qin, W. Lu, Y. Chen, W. Zeng, and P. Yu, “Generalizing to unseen domains: A survey on domain generalization,” IEEE Transactions on Knowledge and Data Engineering
2022
Later among the works it cites.
J. Müller, R. Schmier, L. Ardizzone, C. Rother, and U. Köthe, “Learning robust models using the principle of independent causal mechanisms,” in Pattern Recognition: 43rd DAGM German Conference, DAGM GCPR 2021, Bonn, Germany, September 28–October 1, 2021, Proceedings
2022
Later among the works it cites.
P. Liao, J. Yan, J. M. Sellier, and Y. Zhang, “Divergence-based transferability analysis for self-adaptive smart grid intrusion detection with transfer learning,” IEEE Access
2022
Later among the works it cites.
R. Zhu and S. Li, “Crossmatch: Cross-classifier consistency regularization for open-set single domain generalization,” in International Conference on Learning Representations
2022
Later among the works it cites.
S. Hajifar and H. Sun, “Online domain adaptation for continuous cross-subject liver viability evaluation based on irregular thermal data,” IISE Transactions
2022
Later among the works it cites.
J. Ye, A. Giani, A. Elasser, S. K. Mazumder, C. Farnell, H. A. Mantooth, T. Kim, J. Liu, B. Chen, G.-S. Seo, W. Song, M. D. R. Greidanus, S. Sahoo, F. Blaabjerg, J. Zhang, L. Guo, B. Ahn, M. B. Shadmand, N. R. Gajanur, and M. A. Abbaszada, “A review of cyber–physical security for photovoltaic systems,” IEEE Journal of Emerging and Selected Topics in Power Electronics
2022
Later among the works it cites.
B. Huang and J. Wang, “Applications of physics-informed neural networks in power systems-a review,” IEEE Transactions on Power Systems
2022
Later among the works it cites.
B. Hammi, S. Zeadally, R. Khatoun, and J. Nebhen, “Survey on smart homes: vulnerabilities, risks, and countermeasures,” Computers & Security
2022
Later among the works it cites.
H. Kaushik, T. Kumar, and K. Bhalla, “isecurehome: A deep fusion framework for surveillance of smart homes using real-time emotion recognition,” Applied Soft Computing
2022
Later among the works it cites.
S. Venkatasubramanian, “Ambulatory monitoring of maternal and fetal using deep convolution generative adversarial network for smart health care iot system,” International Journal of Advanced Computer Science and Applications
2022
Later among the works it cites.
I. Pavan Kumar, R. Mahaveerakannan, K. Praveen Kumar, I. Basu, T. C. Anil Kumar, and M. Choche, “A design of disease diagnosis based smart healthcare model using deep learning technique,” in 2022 International Conference on Electronics and Renewable Systems (ICEARS)
2022
Later among the works it cites.
G. Mai, K. Janowicz, Y. Hu, S. Gao, B. Yan, R. Zhu, L. Cai, and N. Lao, “A review of location encoding for geoai: methods and applications,” International Journal of Geographical Information Science
2022
Later among the works it cites.
V. Rondelli, B. Franceschetti, and D. Mengoli, “A review of current and historical research contributions to the development of ground autonomous vehicles for agriculture,” Sustainability
2022
Later among the works it cites.
A. Kumar, S. Singh, M. Yadav, B. Bhuj, S. Dhar, N. Pruthi, R. Kumar, V. Bajpai, M. Rizwan, K. Jyoti, R. S. Thapa, V. Kumar, H. Kumar, B. K. Mishra, V. Kumar, A. Rajput, A. Singh, and R. Kumar, “Artificial intelligence, internet of things (iot) and smart agriculture for sustainable farming: A review,” 2022
2022
Later among the works it cites.
B. B. Sinha and R. Dhanalakshmi, “Recent advancements and challenges of internet of things in smart agriculture: A survey,” Future Generation Computer Systems
2022
Later among the works it cites.
S. Habib, S. Alyahya, M. Islam, A. M. Alnajim, A. Alabdulatif, and A. Alabdulatif, “Design and implementation: An iot-framework-based automated wastewater irrigation system,” Electronics
2022
Later among the works it cites.
F. K. Shaikh, S. Karim, S. Zeadally, and J. Nebhen, “Recent trends in internet of things enabled sensor technologies for smart agriculture,” IEEE Internet of Things Journal
2022
Later among the works it cites.
B. Swaminathan, S. Palani, S. Vairavasundaram, K. Kotecha, and V. Kumar, “Iot-driven artificial intelligence technique for fertilizer recommendation model,” IEEE Consumer Electronics Magazine
2022
Later among the works it cites.
I. Ullah, M. Fayaz, M. Aman, and D. Kim, “An optimization scheme for iot based smart greenhouse climate control with efficient energy consumption,” Computing
2022
Later among the works it cites.
Y. Zhu, A. Abdalla, Z. Tang, and H. Cen, “Improving rice nitrogen stress diagnosis by denoising strips in hyperspectral images via deep learning,” Biosystems Engineering
2022
Later among the works it cites.
O. Elsherbiny, L. Zhou, Y. He, and Z. Qiu, “A novel hybrid deep network for diagnosing water status in wheat crop using iot-based multimodal data,” Computers and Electronics in Agriculture
2022
Later among the works it cites.
S. Fuentes, C. G. Viejo, E. Tongson, and F. R. Dunshea, “The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence,” Animal Health Research Reviews
2022
Later among the works it cites.
Y. Salzer, G. Lidor, L. Rosenfeld, L. Reshef, B. Shaked, J. Grinshpun, H. H. Honig, H. Kamer, M. Balaklav, and M. Ross, “A nose ring sensor system to monitor dairy cow cardiovascular and respiratory metrics,” Journal of Animal Science
2022
Later among the works it cites.
J. Wang, L. Liu, M. Lu, C. Okinda, D. Lovarelli, M. Guarino, and M. Shen, “The estimation of broiler respiration rate based on the semantic segmentation and video amplification,” Frontiers in Physics
2022
Later among the works it cites.
S.-S. Guo, K.-H. Lee, L. Chang, C.-D. Tseng, S.-J. Sie, G.-Z. Lin, J.-Y. Chen, Y.-H. Yeh, Y.-J. Huang, and T.-F. Lee, “Development of an automated body temperature detection platform for face recognition in cattle with yolo v3-tiny deep learning and infrared thermal imaging,” Applied Sciences
2022
Later among the works it cites.
B. Yang and J. Ye, “Data-driven detection of physical faults and cyber attacks in dual-motor ev powertrains,” in 2022 IEEE Transportation Electrification Conference & Expo (ITEC)
2022
Later among the works it cites.
B. Yang, J. Ye, and L. Guo, “Fast detection for cyber threats in electric vehicle traction motor drives,” IEEE Transactions on Transportation Electrification
2022
Later among the works it cites.
B. Yang, J. Ye, S. Coshatt, W. Song, and F. Zahiri, “Data-driven approach for detection of physical faults and cyber attacks in manufacturing motor drives,” in 2022 IEEE Energy Conversion Congress and Exposition (ECCE)
2022
Later among the works it cites.
Q. Li, J. Zhang, J. Ye, and W. Song, “Data-driven cyber-attack detection for photovoltaic systems: A transfer learning approach,” in 2022 IEEE Applied Power Electronics Conference and Exposition (APEC)
2022
Later among the works it cites.
L. Guo, B. Yang, and J. Ye, “Predictive energy management for dual-motor bevs considering temperature-dependent traction inverter loss,” IEEE Transactions on Transportation Electrification
2022
Later among the works it cites.
W. Hong, G. Tao, H. Wang, and C. Wang, “Traffic signal control with adaptive online-learning scheme using multiple-model neural networks,” IEEE Transactions on Neural Networks and Learning Systems
2022
Later among the works it cites.
F. Tajdari, C. Roncoli, and M. Papageorgiou, “Feedback-based ramp metering and lane-changing control with connected and automated vehicles,” IEEE Transactions on Intelligent Transportation Systems
2022
Later among the works it cites.
S. R. Lamooki, S. Hajifar, J. Kang, H. Sun, F. M. Megahed, and L. A. Cavuoto, “A data analytic end-to-end framework for the automated quantification of ergonomic risk factors across multiple tasks using a single wearable sensor,” Applied ergonomics
2022
Later among the works it cites.
H. Ren, J. Deng, and X. Xie, “Grnn: generative regression neural network—a data leakage attack for federated learning,” ACM Transactions on Intelligent Systems and Technology (TIST)
2022
Later among the works it cites.
S. Kumpulainen and V. Terziyan, “Artificial general intelligence vs. industry 4.0: Do they need each other?,” Procedia Computer Science
2022
Later among the works it cites.
M. Hajiha, X. Liu, Y. M. Lee, and M. Ramin, “A physics-regularized data-driven approach for health prognostics of complex engineered systems with dependent health states,” Reliability Engineering & System Safety
2022
Later among the works it cites.
D. Gerhard, T. Köring, and M. Neges, “Generative engineering and design–a comparison of different approaches to utilize artificial intelligence in cad software tools,” in IFIP International Conference on Product Lifecycle Management
2022
Later among the works it cites.
K. Wang, Y. Song, H. Sheng, J. Xu, S. Zhang, and J. Qin, “Energy efficiency design for eco-friendly additive manufacturing based on multimodal attention fusion,” Journal of Manufacturing Processes
2022
Later among the works it cites.
M. Ai, Y. Xie, S. X. Ding, Z. Tang, and W. Gui, “Domain knowledge distillation and supervised contrastive learning for industrial process monitoring,” IEEE Transactions on Industrial Electronics
2022
Later among the works it cites.
Q. Wang, H. Sun, R. Q. Hu, and A. Bhuyan, “When machine learning meets spectrum sharing security: Methodologies and challenges,” IEEE Open Journal of the Communications Society
2022
Later among the works it cites.
M. Aboubakar, M. Kellil, and P. Roux, “A review of iot network management: Current status and perspectives,” Journal of King Saud University-Computer and Information Sciences
2022
Later among the works it cites.
2022
Later among the works it cites.
2022
Later among the works it cites.
G. Lu, S. Li, G. Mai, J. Sun, D. Zhu, L. Chai, H. Sun, X. Wang, H. Dai, N. Liu, et al
2023
Closest in time.
S. Rezayi, Z. Liu, Z. Wu, C. Dhakal, B. Ge, H. Dai, G. Mai, N. Liu, C. Zhen, T. Liu, et al
2023
Closest in time.
J. Ma and B. Wang, “Towards foundation models of biological image segmentation,” Nature Methods
2023
Closest in time.
E. Lehman, E. Hernandez, D. Mahajan, J. Wulff, M. J. Smith, Z. Ziegler, D. Nadler, P. Szolovits, A. Johnson, and E. Alsentzer, “Do we still need clinical language models?,” 2023
2023
Closest in time.
G. Mai, N. Lao, Y. He, J. Song, and S. Ermon, “Csp: Self-supervised contrastive spatial pre-training for geospatial-visual representations,” in International Conference on Machine Learning
2023
Closest in time.
G. Mai, W. Huang, J. Sun, S. Song, D. Mishra, N. Liu, S. Gao, T. Liu, G. Cong, Y. Hu, et al
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
R. Taori, I. Gulrajani, T. Zhang, Y. Dubois, X. Li, C. Guestrin, P. Liang, and T. B. Hashimoto, “Alpaca: A strong, replicable instruction-following model,” Stanford Center for Research on Foundation Models. https://crfm. stanford. edu/2023/03/13/alpaca. html
2023
Closest in time.
2023
Closest in time.
J. Zhang, Z. Zhou, G. Mai, L. Mu, M. Hu, and S. Li, “Text2seg: Remote sensing image semantic segmentation via text-guided visual foundation models,” 2023
2023
Closest in time.
2023
Closest in time.
OpenAI, “Gpt-4 technical report,” arXiv preprint arXiv:2303.08774
2023
Closest in time.
S. Huang, L. Dong, W. Wang, Y. Hao, S. Singhal, S. Ma, T. Lv, L. Cui, O. K. Mohammed, Q. Liu, et al
2023
Closest in time.
2023
Closest in time.
A. P. Murdan, “From smart to intelligent: How internet of things and artificial intelligence are enhancing the modern home,” Journal of Electrical Engineering, Electronics, Control and Computer Science
2023
Closest in time.
2023
Closest in time.
D. Liu, Y. Chen, and Z. Wu, “Digital twin (dt)-cyclegan: Enabling zero-shot sim-to-real transfer of visual grasping models,” IEEE Robotics and Automation Letters
2023
Closest in time.
M. Soori, B. Arezoo, and R. Dastres, “Internet of things for smart factories in industry 4.0, a review,” Internet of Things and Cyber-Physical Systems
2023
Closest in time.
X. Li, L. Zhang, Z. Wu, Z. Liu, L. Zhao, Y. Yuan, J. Liu, G. Li, D. Zhu, P. Yan, et al
2023
Closest in time.
2023
Closest in time.
Y. Liu, T. Han, S. Ma, J. Zhang, Y. Yang, J. Tian, H. He, A. Li, M. He, Z. Liu, et al
2023
Closest in time.
J. Bharadiya, “Artificial intelligence in transportation systems a critical review,” American Journal of Computing and Engineering
2023
Closest in time.
L. Zhao, L. Zhang, Z. Wu, Y. Chen, H. Dai, X. Yu, Z. Liu, T. Zhang, X. Hu, X. Jiang, et al
2023
Closest in time.
C. Zhou, Q. Li, C. Li, J. Yu, Y. Liu, G. Wang, K. Zhang, C. Ji, Q. Yan, L. He, et al
2023
Closest in time.
2023
Closest in time.
A. Mehrish, N. Majumder, R. Bharadwaj, R. Mihalcea, and S. Poria, “A review of deep learning techniques for speech processing,” Information Fusion
2023
Closest in time.
A. Radford, J. W. Kim, T. Xu, G. Brockman, C. McLeavey, and I. Sutskever, “Robust speech recognition via large-scale weak supervision,” in International Conference on Machine Learning
2023
Closest in time.
C. Wang, S. Chen, Y. Wu, Z. Zhang, L. Zhou, S. Liu, Z. Chen, Y. Liu, H. Wang, J. Li, et al
2023
Closest in time.
M. Cascella, G. Scarpati, E. Bignami, A. Cuomo, A. Vittori, P. Gennaro, A. Crispo, and S. Coluccia, “Utilizing an artificial intelligence framework (conditional generative adversarial network) to enhance telemedicine strategies for cancer pain management,” Journal of Anesthesia, Analgesia and Critical Care
2023
Closest in time.
C. Gao, B. D. Killeen, Y. Hu, R. B. Grupp, R. H. Taylor, M. Armand, and M. Unberath, “Synthetic data accelerates the development of generalizable learning-based algorithms for x-ray image analysis,” Nature Machine Intelligence
2023
Closest in time.
T. Nguyen, J. Brandstetter, A. Kapoor, J. K. Gupta, and A. Grover, “Climax: A foundation model for weather and climate,” in International Conference on Machine Learning
2023
Closest in time.
G. Mai, Y. Xuan, W. Zuo, Y. He, J. Song, S. Ermon, K. Janowicz, and N. Lao, “Sphere2vec: A general-purpose location representation learning over a spherical surface for large-scale geospatial predictions,” ISPRS Journal of Photogrammetry and Remote Sensing
2023
Closest in time.
G. Mai, Z. Li, and N. Lao, “Spatial representation learning,” in Handbook of Geospatial Artificial Intelligence (GeoAI)
2023
Closest in time.
P. Kurtser and S. Lowry, “Rgb-d datasets for robotic perception in site-specific agricultural operations—a survey,” Computers and Electronics in Agriculture
2023
Closest in time.
G. Lu, “Bird-view 3d reconstruction for crops with repeated textures,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2023
Closest in time.
G. Lu, “Deep unsupervised visual odometry via bundle adjusted pose graph optimization,” in IEEE International Conference on Robotics and Automation (ICRA)
2023
Closest in time.
R. K. Jain, “Experimental performance of smart iot-enabled drip irrigation system using and controlled through web-based applications,” Smart Agricultural Technology
2023
Closest in time.
V. Kumar, C. Singh, K. R. Rao, M. Kumar, Y. A. Rajwade, B. Babu, and K. Singh, “Evaluation of iot based smart drip irrigation and etc based system for sweet corn,” Smart Agricultural Technology
2023
Closest in time.
R. Jenitha and K. Rajesh, “Intelligent irrigation scheduling scheme based on deep bi-directional lstm technique,” International Journal of Environmental Science and Technology
2023
Closest in time.
T. B. Mary, J. J. Paul, B. Beulah, and J. Joanna, “Iot based weed detection and removal in precision agriculture,” in 2023 2nd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA)
2023
Closest in time.
S. Azfar, A. Nadeem, K. Ahsan, A. Mehmood, M. S. Siddiqui, M. Saeed, and M. Ashraf, “An iot-based system for efficient detection of cotton pest,” Applied Sciences
2023
Closest in time.
R. Arablouei, L. Wang, L. Currie, J. Yates, F. A. Alvarenga, and G. J. Bishop-Hurley, “Animal behavior classification via deep learning on embedded systems,” Computers and Electronics in Agriculture
2023
Closest in time.
M. Shahbazi, K. Mohammadi, S. M. Derakhshani, and P. W. Groot Koerkamp, “Deep learning for laying hen activity recognition using wearable sensors,” Agriculture
2023
Closest in time.
K. Fujinami, R. Takuno, I. Sato, and T. Shimmura, “Evaluating behavior recognition pipeline of laying hens using wearable inertial sensors,” Sensors
2023
Closest in time.
R. Arablouei, Z. Wang, G. J. Bishop-Hurley, and J. Liu, “Multimodal sensor data fusion for in-situ classification of animal behavior using accelerometry and gnss data,” Smart Agricultural Technology
2023
Closest in time.
2023
Closest in time.
Y. Shao, A. Cook, C. Wang, J. Chen, A. Zhou, D. Deter, N. Perry, B. Thompson, and USDOE Office of Energy Efficiency and Renewable Energy, “Real-sim flexible interface for x-in-the-loop simulation (fixs),” 7 2023
2023
Closest in time.
Y. Hu, J. Yang, L. Chen, K. Li, C. Sima, X. Zhu, S. Chai, S. Du, T. Lin, W. Wang, L. Lu, X. Jia, Q. Liu, J. Dai, Y. Qiao, and H. Li, “Planning-oriented autonomous driving,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2023
Closest in time.
J. Klender, “Tesla full self-driving to feature ”end-to-end ai“ with groundbreaking v12 release,” 2023
2023
Closest in time.
S. Badini, S. Regondi, E. Frontoni, and R. Pugliese, “Assessing the capabilities of chatgpt to improve additive manufacturing troubleshooting,” Advanced Industrial and Engineering Polymer Research
2023
Closest in time.
L. J. Segura, Z. Li, C. Zhou, and H. Sun, “Droplet evolution prediction in material jetting via tensor time series analysis,” Additive Manufacturing
2023
Closest in time.
S. K. Kheiri, Z. Vahedi, H. Sun, F. M. Megahed, and L. A. Cavuoto, “Human reliability modeling in occupational environments toward a safe and productive operator 4.0,” International Journal of Industrial Ergonomics
2023
Closest in time.
Z. Vahedi, S. Kazemi Kheiri, S. Hajifar, S. Ragani Lamooki, H. Sun, F. M. Megahed, and L. A. Cavuoto, “The relationship between ratings of perceived exertion (rpe) and relative strength for a fatiguing dynamic upper extremity task: A consideration of multiple cycles and conditions,” Journal of Occupational and Environmental Hygiene
2023
Closest in time.
J. D. Toscano, C. Zuniga-Navarrete, W. D. J. Siu, L. J. Segura, and H. Sun, “Teeth mold point cloud completion via data augmentation and hybrid rl-gan,” Journal of Computing and Information Science in Engineering
2023
Closest in time.
J. Chung, B. Shen, and Z. J. Kong, “Anomaly detection in additive manufacturing processes using supervised classification with imbalanced sensor data based on generative adversarial network,” Journal of Intelligent Manufacturing
2023
Closest in time.
Z. Li, L. J. Segura, Y. Li, C. Zhou, and H. Sun, “Multiclass reinforced active learning for droplet pinch-off behaviors identification in inkjet printing,” Journal of Manufacturing Science and Engineering
2023
Closest in time.
Z. Li, F. Yao, and H. Sun, “Reinforced active learning for cvd-grown two-dimensional materials characterization,” IISE Transactions
2023
Closest in time.
2023
Closest in time.
B. Rathore, “Future of textile: Sustainable manufacturing & prediction via chatgpt,” Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal
2023
Closest in time.
G. Eysenbach et al
2023
Closest in time.
D. Baidoo-Anu and L. Owusu Ansah, “Education in the era of generative artificial intelligence (ai): Understanding the potential benefits of chatgpt in promoting teaching and learning,” Available at SSRN 4337484
2023
Closest in time.
G. Cooper, “Examining science education in chatgpt: An exploratory study of generative artificial intelligence,” Journal of Science Education and Technology
2023
Closest in time.
N. El-Haggar, L. Amouri, A. Alsumayt, F. H. Alghamedy, and S. S. Aljameel, “The effectiveness and privacy preservation of iot on ubiquitous learning: Modern learning paradigm to enhance higher education,” Applied Sciences
2023
Closest in time.
X. Zhai, “Chatgpt and ai: The game changer for education,” Available at SSRN
2023
Closest in time.
X. Zhai, “Chatgpt for next generation science learning,” XRDS: Crossroads, The ACM Magazine for Students
2023
Closest in time.
S. Atlas, “Chatgpt for higher education and professional development: A guide to conversational ai,” 2023
2023
Closest in time.
H. Xie, M. Xia, P. Wu, S. Wang, and H. V. Poor, “Edge learning for large-scale internet of things with task-oriented efficient communication,” IEEE Transactions on Wireless Communications
2023
Closest in time.