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This paper proposes a Fast Region-based Convolutional Network method (Fast R-CNN) for object detection.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. Boser, J. Denker, D. Henderson, R. Howard, W. Hubbard, and L. Jackel · 1989
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Multitask learning
R. Caruana · 1997
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Rapid object detection using a boosted cascade of simple features
P. Viola and M. Jones · 2001
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Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
S. Lazebnik, C. Schmid, and J. Ponce · 2006
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ImageNet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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The PASCAL Visual Object Classes (VOC) Challenge
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
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Object detection with discriminatively trained part based models
P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan · 2010
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Semantic segmentation with second-order pooling
J. Carreira, R. Caseiro, J. Batista, and C. Sminchisescu · 2012
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ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. Hinton · 2012
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Do we need more training data or better models for object detection?
X. Zhu, C. Vondrick, D. Ramanan, and C. Fowlkes · 2012
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Selective search for object recognition
J. Uijlings, K. van de Sande, T. Gevers, and A. Smeulders · 2013
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Restructuring of deep neural network acoustic models with singular value decomposition
J. Xue, J. Li, and Y. Gong · 2013
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Return of the devil in the details: Delving deep into convolutional nets
K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
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Exploiting linear structure within convolutional networks for efficient evaluation
E. Denton, W. Zaremba, J. Bruna, Y. LeCun, and R. Fergus · 2014
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Scalable object detection using deep neural networks
D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov · 2014
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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Network in network
M. Lin, Q. Chen, and S. Yan · 2014
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Microsoft COCO: common objects in context
T. Lin, M. Maire, S. Belongie, L. Bourdev, R. Girshick, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2014
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Region-based convolutional networks for accurate object detection and segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2015
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
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J. H. Hosang, R. Benenson, P. Dollár, and B. Schiele · 2015
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
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segDeepM: Exploiting segmentation and context in deep neural networks for object detection
Y. Zhu, R. Urtasun, R. Salakhutdinov, and S. Fidler · 2015
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