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The design of neural network architectures is an important component for achieving state-of-the-art performance with machine learning systems across a broad array of tasks.
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Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
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Learning hierarchical features for scene labeling
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Fast image scanning with deep max-pooling convolutional neural networks
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2d human pose estimation: New benchmark and state of the art analysis
M. Andriluka, L. Pishchulin, P. Gehler, and B. Schiele · 2014
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Detect what you can: Detecting and representing objects using holistic models and body parts
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The pascal visual object classes challenge – a retrospective
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Microsoft coco: Common objects in context
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Recurrent convolutional neural networks for scene labeling
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Overfeat: Integrated recognition, localization and detection using convolutional networks
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Rigid-motion scattering for image classification
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Sequence to sequence learning with neural networks
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Segnet: A deep convolutional encoder-decoder architecture for image segmentation
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Material recognition in the wild with the materials in context database
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Semantic image segmentation with deep convolutional nets and fully connected crfs
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Convolutional feature masking for joint object and stuff segmentation
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Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
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Batch normalization: accelerating deep network training by reducing internal covariate shift
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Parsenet: Looking wider to see better
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Semantic image segmentation via deep parsing network
Z. Liu, X. Li, P. Luo, C. C. Loy, and X. Tang · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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Feedforward semantic segmentation with zoom-out features
M. Mostajabi, P. Yadollahpour, and G. Shakhnarovich · 2015
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Modeling local and global deformations in deep learning: Epitomic convolution, multiple instance learning, and sliding window detection
G. Papandreou, I. Kokkinos, and P.-A. Savalle · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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U-net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Mobilenets: Efficient convolutional neural networks for mobile vision applications
A. G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam · 2017
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Densely connected convolutional networks
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Interpretable structure-evolving lstm
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Refinenet: Multi-path refinement networks with identity mappings for high-resolution semantic segmentation
G. Lin, A. Milan, C. Shen, and I. Reid · 2017
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R. Miikkulainen, J. Liang, E. Meyerson, A. Rawal, D. Fink, O. Francon, B. Raju, H. Shahrzad, A. Navruzyan, N. Duffy, and B. Hodjat · 2017
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Cited alongside, same era.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
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Fully connected deep structured networks
A. G. Schwing and R. Urtasun · 2015
Cited alongside, same era.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
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Conditional random fields as recurrent neural networks
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Cited alongside, same era.
Listen, attend and spell: A neural network for large vocabulary conversational speech recognition
W. Chan, N. Jaitly, Q. Le, and O. Vinyals · 2016
Cited alongside, same era.
Attention to scale: Scale-aware semantic image segmentation
L.-C. Chen, Y. Yang, J. Wang, W. Xu, and A. L. Yuille · 2016
Cited alongside, same era.
Deeparchitect: Automatically designing and training deep architectures
R. Negrinho and G. Gordon · 2017
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Large kernel matters–improve semantic segmentation by global convolutional network
C. Peng, X. Zhang, G. Yu, G. Luo, and J. Sun · 2017
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Deformable convolutional networks – coco detection and segmentation challenge 2017 entry
H. Qi, Z. Zhang, B. Xiao, H. Hu, B. Cheng, Y. Wei, and J. Dai · 2017
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Large-scale evolution of image classifiers
E. Real, S. Moore, A. Selle, S. Saxena, Y. L. Suematsu, J. Tan, Q. Le, and A. Kurakin · 2017
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Understanding convolution for semantic segmentation
P. Wang, P. Chen, Y. Yuan, D. Liu, Z. Huang, X. Hou, and G. Cottrell · 2017
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Joint multi-person pose estimation and semantic part segmentation
F. Xia, P. Wang, X. Chen, and A. L. Yuille · 2017
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Genetic cnn
L. Xie and A. Yuille · 2017
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Pyramid scene parsing network
H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia · 2017
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Neural architecture search with reinforcement learning
B. Zoph and Q. V. Le · 2017
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In-place activated batchnorm for memory-optimized training of dnns
S. R. Bulò, L. Porzi, and P. Kontschieder · 2018
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Efficient architecture search by network transformation
H. Cai, T. Chen, W. Zhang, Y. Yu, and J. Wang · 2018
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Masklab: Instance segmentation by refining object detection with semantic and direction features
L.-C. Chen, A. Hermans, G. Papandreou, F. Schroff, P. Wang, and H. Adam · 2018
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Encoder-decoder with atrous separable convolution for semantic image segmentation
L.-C. Chen, Y. Zhu, G. Papandreou, F. Schroff, and H. Adam · 2018
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Weakly and semi supervised human body part parsing via pose-guided knowledge transfer
H.-S. Fang, G. Lu, X. Fang, J. Xie, Y.-W. Tai, and C. Lu · 2018
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Multi-scale context intertwining for semantic segmentation
D. Lin, Y. Ji, D. Lischinski, D. Cohen-Or, and H. Huang · 2018
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Progressive neural architecture search
C. Liu, B. Zoph, M. Neumann, J. Shlens, W. Hua, L.-J. Li, L. Fei-Fei, A. Yuille, J. Huang, and K. Murphy · 2018
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Hierarchical representations for efficient architecture search
H. Liu, K. Simonyan, O. Vinyals, C. Fernando, and K. Kavukcuoglu · 2018
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Darts: Differentiable architecture search
H. Liu, K. Simonyan, and Y. Yang · 2018
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Personlab: Person pose estimation and instance segmentation with a bottom-up, part-based, geometric embedding model
G. Papandreou, T. Zhu, L.-C. Chen, S. Gidaris, J. Tompson, and K. Murphy · 2018
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Efficient neural architecture search via parameter sharing
H. Pham, M. Y. Guan, B. Zoph, Q. V. Le, and J. Dean · 2018
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Regularized evolution for image classifier architecture search
E. Real, A. Aggarwal, Y. Huang, and Q. V. Le · 2018
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Mobilenetv2: Inverted residuals and linear bottlenecks
M. Sandler, A. Howard, M. Zhu, A. Zhmoginov, and L.-C. Chen · 2018
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Denseaspp for semantic segmentation in street scenes
M. Yang, K. Yu, C. Zhang, Z. Li, and K. Yang · 2018
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Learning a discriminative feature network for semantic segmentation
C. Yu, J. Wang, C. Peng, C. Gao, G. Yu, and N. Sang · 2018
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Context encoding for semantic segmentation
H. Zhang, K. Dana, J. Shi, Z. Zhang, X. Wang, A. Tyagi, and A. Agrawal · 2018
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Exfuse: Enhancing feature fusion for semantic segmentation
Z. Zhang, X. Zhang, C. Peng, D. Cheng, and J. Sun · 2018
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Practical network blocks design with q-learning
Z. Zhong, J. Yan, and C.-L. Liu · 2018
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Learning transferable architectures for scalable image recognition
B. Zoph, V. Vasudevan, J. Shlens, and Q. V. Le · 2018
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