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Fine-grained image labels are desirable for many computer vision applications, such as visual search or mobile AI assistant.
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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Adaptive subgradient methods for online learning and stochastic optimization
J. Duchi, E. Hazan, and Y. Singer · 2011
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Do deep nets really need to be deep?
J. Ba and R. Caruana · 2014
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Learning and transferring mid-level image representations using convolutional neural networks
M. Oquab, L. Bottou, I. Laptev, and J. Sivic · 2014
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Fitnets: Hints for thin deep nets
A. Romero, N. Ballas, S. E. Kahou, A. Chassang, C. Gatta, and Y. Bengio · 2014
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Cnn features off-the-shelf: an astounding baseline for recognition
A. Sharif Razavian, H. Azizpour, J. Sullivan, and S. Carlsson · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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How transferable are features in deep neural networks?
J. Yosinski, J. Clune, Y. Bengio, and H. Lipson · 2014
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Part-based r-cnns for fine-grained category detection
N. Zhang, J. Donahue, R. Girshick, and T. Darrell · 2014
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Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2015
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Bilinear cnn models for fine-grained visual recognition
T.-Y. Lin, A. RoyChowdhury, and S. Maji · 2015
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A. A. Rusu, S. G. Colmenarejo, C. Gulcehre, G. Desjardins, J. Kirkpatrick, R. Pascanu, V. Mnih, K. Kavukcuoglu, and R. Hadsell · 2015
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Hd-cnn: Hierarchical deep convolutional neural networks for large scale visual recognition
Z. Yan, H. Zhang, R. Piramuthu, V. Jagadeesh, D. DeCoste, W. Di, and Y. Yu · 2015
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Learning without forgetting
Z. Li and D. Hoiem · 2016
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Rethinking the inception architecture for computer vision
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna · 2016
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Fine-grained image classification by exploring bipartite-graph labels
F. Zhou and Y. Lin · 2016
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Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition
J. Fu, H. Zheng, and T. Mei · 2017
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Fine-grained image classification via combining vision and language
X. He and Y. Peng · 2017
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Densely connected convolutional networks
G. Huang, Z. Liu, L. van der Maaten, and K. Q. Weinberger · 2017
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Network of experts for large-scale image categorization
K. Ahmed, M. H. Baig, and L. Torresani · 2016
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Factors of transferability for a generic convnet representation
H. Azizpour, A. S. Razavian, J. Sullivan, A. Maki, and S. Carlsson · 2016
Cited alongside, same era.
Fine-grained categorization and dataset bootstrapping using deep metric learning with humans in the loop
Y. Cui, F. Zhou, Y. Lin, and S. Belongie · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Revisiting unreasonable effectiveness of data in deep learning era
C. Sun, A. Shrivastava, S. Singh, and A. Gupta · 2017
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Growing a brain: Fine-tuning by increasing model capacity
Y.-X. Wang, D. Ramanan, and M. Hebert · 2017
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