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Complex activities of daily living (ADLs) often consist of multiple micro-activities.
Zero-data learning of new tasks.. In AAAI , Vol. 1. 3
Hugo Larochelle, Dumitru Erhan, and Yoshua Bengio. 2008 · 2008
Earlier work this paper cites.
SVM-based multimodal classification of activities of daily living in health smart homes: sensors, algorithms, and first experimental results
Anthony Fleury, Michel Vacher, and Norbert Noury. 2009 · 2009
Earlier work this paper cites.
Tim Sainburg, Leland McInnes, and Timothy Q. Gentner. 2020 · 2009
Earlier work this paper cites.
Temporal segmentation and activity classification from first-person sensing. In 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops . IEEE, 17–24
Ekaterina H Spriggs, Fernando De La Torre, and Martial Hebert. 2009 · 2009
Earlier work this paper cites.
Hubs in space: Popular nearest neighbors in high-dimensional data
Milos Radovanovic, Alexandros Nanopoulos, and Mirjana Ivanovic. 2010 · 2010
Earlier work this paper cites.
Collecting complex activity datasets in highly rich networked sensor environments. In 2010 Seventh international conference on networked sensing systems (INSS) . IEEE, 233–240
Daniel Roggen, Alberto Calatroni, Mirco Rossi, Thomas Holleczek, Kilian Förster, Gerhard Tröster, Paul Lukowicz, David Bannach, Gerald Pirkl, Alois Ferscha, et al · 2010
Earlier work this paper cites.
Pbn: towards practical activity recognition using smartphone-based body sensor networks. In Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems . 246–259
Matthew Keally, Gang Zhou, Guoliang Xing, Jianxin Wu, and Andrew Pyles. 2011 · 2011
Earlier work this paper cites.
Optimal detection of changepoints with a linear computational cost
Rebecca Killick, Paul Fearnhead, and Idris A Eckley. 2012 · 2012
Earlier work this paper cites.
Automatic Annotation of Sensor Data Streams using Abductive Reasoning.. In KEOD . 345–354
Marjan Alirezaie and Amy Loutfi. 2013 · 2013
Earlier work this paper cites.
Towards zero-shot learning for human activity recognition using semantic attribute sequence model. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing . 355–358
Heng-Tze Cheng, Martin Griss, Paul Davis, Jianguo Li, and Di You. 2013 · 2013
Earlier work this paper cites.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
Earlier work this paper cites.
Complex activity recognition using context-driven activity theory and activity signatures
Saguna Saguna, Arkady Zaslavsky, and Dipanjan Chakraborty. 2013 · 2013
Earlier work this paper cites.
Relative density-ratio estimation for robust distribution comparison
Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, and Masashi Sugiyama. 2013 · 2013
Earlier work this paper cites.
SensTrack: Energy-efficient location tracking with smartphone sensors
Lei Zhang, Jiangchuan Liu, Hongbo Jiang, and Yong Guan. 2013 · 2013
Earlier work this paper cites.
Improving zero-shot learning by mitigating the hubness problem
Georgiana Dinu, Angeliki Lazaridou, and Marco Baroni. 2014 · 2014
Earlier work this paper cites.
Glove: Global vectors for word representation. In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP) . 1532–1543
Jeffrey Pennington, Richard Socher, and Christopher D Manning. 2014 · 2014
Earlier work this paper cites.
A-Wristocracy: Deep learning on wrist-worn sensing for recognition of user complex activities. In 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) . 1–6
Praneeth Vepakomma, Debraj De, Sajal K. Das, and Shekhar Bhansali. 2015 · 2015
Earlier work this paper cites.
Recognizing Complex Activities by a Probabilistic Interval-Based Model
Li Liu, Li Cheng, Ye Liu, Yongpo Jia, and David Rosenblum. 2016a · 2016
Earlier work this paper cites.
Complex activity recognition using time series pattern dictionary learned from ubiquitous sensors
Li Liu, Yuxin Peng, Shu Wang, Ming Liu, and Zigang Huang. 2016b · 2016
Earlier work this paper cites.
Mining intricate temporal rules for recognizing complex activities of daily living under uncertainty
Li Liu, Shu Wang, Yuxin Peng, Zigang Huang, Ming Liu, and Bin Hu. 2016c · 2016
Cited alongside, same era.
Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments
Nirmalya Roy, Archan Misra, and Diane Cook. 2016 · 2016
Cited alongside, same era.
Latent embeddings for zero-shot classification. In Proceedings of the IEEE conference on computer vision and pattern recognition . 69–77
Yongqin Xian, Zeynep Akata, Gaurav Sharma, Quynh Nguyen, Matthias Hein, and Bernt Schiele. 2016 · 2016
Cited alongside, same era.
New efficient algorithms for multiple change-point detection with kernels
Alain Celisse, Guillemette Marot, Morgane Pierre-Jean, and Guillem Rigaill. 2017 · 2017
Cited alongside, same era.
Active learning enabled activity recognition
HM Sajjad Hossain, Md Abdullah Al Hafiz Khan, and Nirmalya Roy. 2017 · 2017
Espresso: Entropy and shape aware time-series segmentation for processing heterogeneous sensor data
Shohreh Deldari, Daniel V Smith, Amin Sadri, and Flora Salim. 2020 · 2020
Later among the works it cites.
Cooking activity dataset with macro and micro activities
Paula Lago, Shingo Takeda, Kohei Adachi, Sayeda Shamma Alia, Moe Matsuki, Brahim Benai, Sozo Inoue, and Francois Charpillet. 2020 · 2020
Later among the works it cites.
Lara: Creating a dataset for human activity recognition in logistics using semantic attributes
Friedrich Niemann, Christopher Reining, Fernando Moya Rueda, Nilah Ravi Nair, Janine Anika Steffens, Gernot A Fink, and Michael Ten Hompel. 2020 · 2020
Later among the works it cites.
Annotation Performance for multi-channel time series HAR Dataset in Logistics. In 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) . 1–6
Christopher Reining, Fernando Moya Rueda, Friedrich Niemann, Gernot A. Fink, and Michael ten Hompel. 2020 · 2020
Later among the works it cites.
Selective review of offline change point detection methods
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Cited alongside, same era.
Towards complex activity recognition using a Bayesian network-based probabilistic generative framework
Li Liu, Shu Wang, Guoxin Su, Zi-Gang Huang, and Ming Liu. 2017 · 2017
Cited alongside, same era.
A dataset for activity recognition in an unmodified kitchen using smart-watch accelerometers. In Proceedings of the 16th International Conference on Mobile and Ubiquitous Multimedia . 63–68
Yasser Mohammad, Kazunori Matsumoto, and Keiichiro Hoashi. 2017 · 2017
Cited alongside, same era.
The experience sampling method on mobile devices
Niels Van Berkel, Denzil Ferreira, and Vassilis Kostakos. 2017 · 2017
Cited alongside, same era.
Zero-shot human activity recognition via nonlinear compatibility based method. In Proceedings of the International Conference on Web Intelligence . 322–330
Wei Wang, Chunyan Miao, and Shuji Hao. 2017 · 2017
Cited alongside, same era.
Zero-Shot Activity Recognition with Verb Attribute Induction. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing . 946–958
Rowan Zellers and Yejin Choi. 2017 · 2017
Cited alongside, same era.
UMAP: Uniform Manifold Approximation and Projection
Leland McInnes, John Healy, Nathaniel Saul, and Lukas Grossberger. 2018 · 2018
Cited alongside, same era.
Learning attribute representation for human activity recognition. In 2018 24th International Conference on Pattern Recognition (ICPR) . IEEE, 523–528
Fernando Moya Rueda and Gernot A Fink. 2018 · 2018
Cited alongside, same era.
Charles Truong, Laurent Oudre, and Nicolas Vayatis. 2020 · 2020
Later among the works it cites.
SyncWISE: Window Induced Shift Estimation for Synchronization of Video and Accelerometry from Wearable Sensors
Yun C Zhang, Shibo Zhang, Miao Liu, Elyse Daly, Samuel Battalio, Santosh Kumar, Bonnie Spring, James M Rehg, and Nabil Alshurafa. 2020 · 2020
Later among the works it cites.
Designing memory aids for dementia patients using earables. In Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers . 152–157
Matija Franklin, David Lagnado, Chulhong Min, Akhil Mathur, and Fahim Kawsar. 2021 · 2021
Later among the works it cites.
Recognizing Complex Activities by a Temporal Causal Network-Based Model. In Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track . Springer International Publishing, 341–357
Jun Liao, Junfeng Hu, and Li Liu. 2021 · 2021
Later among the works it cites.
Zero-shot learning for imu-based activity recognition using video embeddings
Catherine Tong, Jinchen Ge, and Nicholas D Lane. 2021 · 2021
Later among the works it cites.
Detecting Anomalies in Daily Activity Routines of Older Persons in Single Resident Smart Homes: Proof-of-Concept Study
Zahraa Khais Shahid, Saguna Saguna, and Christer Åhlund. 2022 · 2022
Later among the works it cites.
Acconotate: Exploiting Acoustic Changes for Automatic Annotation of Inertial Data at the Source. In 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) . 25–33
Soumyajit Chatterjee, Arun Singh, Bivas Mitra, and Sandip Chakraborty. 2023 · 2023
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