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Convolutional Neural Networks (CNNs) use pooling to decrease the size of activation maps.
Outline of a theory of statistical estimation based on the classical theory of probability
Jerzy Neyman · 1937
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Note on the sampling error of the difference between correlated proportions or percentages
Quinn McNemar · 1947
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Note on the “correction for continuity” in testing the significance of the difference between correlated proportions
Allen L Edwards · 1948
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Least squares quantization in PCM
Stuart Lloyd · 1982
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Statistical methods for research workers
Ronald Aylmer Fisher · 1992
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Hierarchical models of object recognition in cortex
Maximilian Riesenhuber and Tomaso Poggio · 1999
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Principal component analysis
IT Jolliffe · 2003
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Visual categorization with bags of keypoints
Gabriella Csurka, Christopher Dance, Lixin Fan, Jutta Willamowski, and Cédric Bray · 2004
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Object recognition with features inspired by visual cortex
Thomas Serre, Lior Wolf, and Tomaso Poggio · 2005
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Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce · 2006
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Significance level
Robert M Craparo · 2007
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Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
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Linear spatial pyramid matching using sparse coding for image classification
Jianchao Yang, Kai Yu, Yihong Gong, and Thomas Huang · 2009
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Visualizing higher-layer features of a deep network
Dumitru Erhan, Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2009
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A theoretical analysis of feature pooling in visual recognition
Y-Lan Boureau, Jean Ponce, and Yann LeCun · 2010
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Locality-constrained linear coding for image classification
Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv, Thomas Huang, and Yihong Gong · 2010
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UCF101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
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Stochastic pooling for regularization of deep convolutional neural networks
Matthew D Zeiler and Robert Fergus · 2013
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
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Signal recovery from pooling representations
Joan Bruna Estrach, Arthur Szlam, and Yann LeCun · 2014
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Learned-norm pooling for deep feedforward and recurrent neural networks
Caglar Gulcehre, Kyunghyun Cho, Razvan Pascanu, and Yoshua Bengio · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Mixed pooling for convolutional neural networks
Dingjun Yu, Hanli Wang, Peiqiu Chen, and Zhihua Wei · 2014
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Single image super-resolution from transformed self-exemplars
Jia-Bin Huang, Abhishek Singh, and Narendra Ahuja · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Detail-preserving pooling in deep networks
Faraz Saeedan, Nicolas Weber, Michael Goesele, and Stefan Roth · 2018
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A closer look at spatiotemporal convolutions for action recognition
Du Tran, Heng Wang, Lorenzo Torresani, Jamie Ray, Yann LeCun, and Manohar Paluri · 2018
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A short note on the Kinetics-700 human action dataset
Joao Carreira, Eric Noland, Chloe Hillier, and Andrew Zisserman · 2019
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Ordinal pooling
Adrien Deliège, Maxime Istasse, Ashwani Kumar, Christophe De Vleeschouwer, and Marc Van Droogenbroeck · 2019
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SlowFast networks for video recognition
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He · 2019
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Lip: Local importance-based pooling
Ziteng Gao, Limin Wang, and Gangshan Wu · 2019
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Understanding intra-class knowledge inside CNN
Donglai Wei, Bolei Zhou, Antonio Torrabla, and William Freeman · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Generalizing pooling functions in convolutional neural networks: Mixed, gated, and tree
Chen-Yu Lee, Patrick W Gallagher, and Zhuowen Tu · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
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Large-scale weakly-supervised pre-training for video action recognition
Deepti Ghadiyaram, Du Tran, and Dhruv Mahajan · 2019
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Global feature guided local pooling
Takumi Kobayashi · 2019
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Regularized evolution for image classifier architecture search
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V Le · 2019
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Analyzing human-human interactions: A survey
Alexandros Stergiou and Ronald Poppe · 2019
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Video classification with channel-separated convolutional networks
Du Tran, Heng Wang, Lorenzo Torresani, and Matt Feiszli · 2019
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HACS: Human action clips and segments dataset for recognition and temporal localization
Hang Zhao, Antonio Torralba, Lorenzo Torresani, and Zhicheng Yan · 2019
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Class feature pyramids for video explanation
Alexandros Stergiou, Georgios Kapidis, Grigorios Kalliatakis, Christos Chrysoulas, Ronald Poppe, and Remco Veltkamp · 2019
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Saliency tubes: Visual explanations for spatio-temporal convolutions
Alexandros Stergiou, Georgios Kapidis, Grigorios Kalliatakis, Christos Chrysoulas, Remco Veltkamp, and Ronald Poppe · 2019
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Would mega-scale datasets further enhance spatiotemporal 3d cnns?
Hirokatsu Kataoka, Tenga Wakamiya, Kensho Hara, and Yutaka Satoh · 2020
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A multigrid method for efficiently training video models
Chao-Yuan Wu, Ross Girshick, Kaiming He, Christoph Feichtenhofer, and Philipp Krähenbühl · 2020
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Learn to cycle: Time-consistent feature discovery for action recognition
Alexandros Stergiou and Ronald Poppe · 2021
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LiftPool: Bidirectional convnet pooling
Jiaojiao Zhao and Cees G. Snoek · 2021
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Chi-square distribution table
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The mind’s eye: Visualizing class-agnostic features of cnns
Alexandros Stergiou · 2021
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