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We revisit the importance of the individual units in Convolutional Neural Networks (CNNs) for visual recognition.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2013
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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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Cnn features off-the-shelf: an astounding baseline for recognition
A. S. Razavian, H. Azizpour, J. Sullivan, and S. Carlsson · 2014
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Deep inside convolutional networks: Visualising image classification models and saliency maps
K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
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Dropout: a simple way to prevent neural networks from overfitting
N. Srivastava, G. E. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 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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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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Learning both weights and connections for efficient neural network
S. Han, J. Pool, J. Tran, and W. Dally · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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Convergent learning: Do different neural networks learn the same representations?
Y. Li, J. Yosinski, J. Clune, H. Lipson, and J. Hopcroft · 2015
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Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, et al · 2015
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Object detectors emerge in deep scene cnns
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba · 2015
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Pruning filters for efficient convnets
H. Li, A. Kadav, I. Durdanovic, H. Samet, and H. P. Graf · 2016
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Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
A. Nguyen, A. Dosovitskiy, J. Yosinski, T. Brox, and J. Clune · 2016
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Network dissection: Quantifying interpretability of deep visual representations
D. Bau, B. Zhou, A. Khosla, A. Oliva, and A. Torralba · 2017
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Feature visualization. distill, 2017
C. Olah, A. Mordvintsev, and L. Schubert · 2017
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Understanding deep learning requires rethinking generalization
C. Zhang, S. Bengio, M. Hardt, B. Recht, and O. Vinyals · 2017
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Region-based convolutional networks for accurate object detection and segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2016
Cited alongside, same era.
Dsd: Dense-sparse-dense training for deep neural networks
S. Han, J. Pool, S. Narang, H. Mao, E. Gong, S. Tang, E. Elsen, P. Vajda, M. Paluri, J. Tran, et al · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
B. Zhou, A. Lapedriza, A. Khosla, A. Oliva, and A. Torralba · 2017
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On the importance of single directions for generalization
A. S. Morcos, D. G. Barrett, N. C. Rabinowitz, and M. Botvinick · 2018
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