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Image segmentation is an important step in most visual tasks.
Learning long-term dependencies with gradient descent is difficult
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Ilya Sutskever, James Martens, and Geoffrey E Hinton · 2011
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Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Oriol Vinyals, Suman V Ravuri, and Daniel Povey · 2012
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Adadelta: an adaptive learning rate method
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Fuxin Li, Taeyoung Kim, Ahmad Humayun, David Tsai, and James M Rehg · 2013
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Kyunghyun Cho, Bart van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio · 2014
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Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, and Li Fei-Fei · 2014
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Modeling deep temporal dependencies with recurrent grammar cells””
Vincent Michalski, Roland Memisevic, and Kishore Konda · 2014
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Densecap: Fully convolutional localization networks for dense captioning
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Guosheng Lin, Chunhua Shen, Ian Reid, et al · 2015
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A benchmark dataset and evaluation methodology for video object segmentation
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Going deeper with convolutions
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Lijun Wang, Wanli Ouyang, Xiaogang Wang, and Huchuan Lu · 2015
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Conditional random fields as recurrent neural networks
Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, and Philip HS Torr · 2015
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