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Deep reinforcement learning has become popular over recent years, showing superiority on different visual-input tasks such as playing Atari games and robot navigation.
Backpropagation applied to handwritten zip code recognition
Yann LeCun, Bernhard Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne Hubbard, and Lawrence D Jackel · 1989
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
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Generalization in reinforcement learning: Successful examples using sparse coarse coding
Richard S Sutton · 1996
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 1998
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Example-based object detection in images by components
Anuj Mohan, Constantine Papageorgiou, and Tomaso Poggio · 2001
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Robust Registration of Multi-modal Images: Towards Real-Time Clinical Applications
Sébastien Ourselin, Radu Stefanescu, and Xavier Pennec · 2002
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Learning to parse pictures of people
Rémi Ronfard, Cordelia Schmid, and Bill Triggs · 2002
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J. 4 supervised actor-critic reinforcement learning
MTRAG Barto · 2004
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Distinctive image features from scale-invariant keypoints
David G Lowe · 2004
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Human detection based on a probabilistic assembly of robust part detectors
Krystian Mikolajczyk, Cordelia Schmid, and Andrew Zisserman · 2004
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Histograms of oriented gradients for human detection
Navneet Dalal and Bill Triggs · 2005
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Neural fitted q iteration–first experiences with a data efficient neural reinforcement learning method
Martin Riedmiller · 2005
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Template Matching Techniques in Computer Vision: Theory and Practice
Roberto Brunelli · 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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version 7.10.0 (R2010a)
MATLAB · 2010
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Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R Salakhutdinov · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Fast-match: Fast affine template matching
Simon Korman, Daniel Reichman, Gilad Tsur, and Shai Avidan · 2013
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Building high-level features using large scale unsupervised learning
Quoc V Le · 2013
On learning to localize objects with minimal supervision
Hyun Oh Song, Ross B Girshick, Stefanie Jegelka, Julien Mairal, Zaid Harchaoui, Trevor Darrell, et al · 2014
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Visualizing and understanding convolutional networks
Matthew D Zeiler and Rob Fergus · 2014
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Fast r-cnn
Ross Girshick · 2015
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Open source computer vision library
Itseez · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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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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Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun · 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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Selective search for object recognition
Jasper RR Uijlings, Koen EA van de Sande, Theo Gevers, and Arnold WM Smeulders · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
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Learning rich features from rgb-d images for object detection and segmentation
Saurabh Gupta, Ross Girshick, Pablo Arbeláez, and Jitendra Malik · 2014
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Deep fragment embeddings for bidirectional image sentence mapping
Andrej Karpathy, Armand Joulin, and Fei Fei F Li · 2014
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Deep reinforcement learning with double q-learning
Hado van Hasselt, Arthur Guez, and David Silver · 2015
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Dueling network architectures for deep reinforcement learning
Ziyu Wang, Nando de Freitas, and Marc Lanctot · 2015
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Playing fps games with deep reinforcement learning
Guillaume Lample and Devendra Singh Chaplot · 2016
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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Why should i trust you?: Explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
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