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Deep residual networks have recently shown appealing performance on many challenging computer vision tasks.
Theory of the backpropagation neural network
Hecht-Nielsen, R.: · 1989
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Learning multiple layers of features from tiny images (2009)
Krizhevsky, A.: · 2009
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Understanding the difficulty of training deep feedforward neural networks
Glorot, X., Bengio, Y.: · 2010
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Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
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Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2014
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Caffe: Convolutional architecture for fast feature embedding
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., Darrell, T.: · 2014
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Lee, C.Y., Xie, S., Gallagher, P., Zhang, Z., Tu, Z.: · 2014
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Imagenet large scale visual recognition challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al.: · 2015
Cited alongside, same era.
Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., Sun, J.: · 2015
Cited alongside, same era.
Instance-aware semantic segmentation via multi-task network cascades
Dai, J., He, K., Sun, J.: · 2015
Cited alongside, same era.
Faster r-cnn: Towards real-time object detection with region proposal networks
Ren, S., He, K., Girshick, R., Sun, J.: · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, S., Szegedy, C.: · 2015
Cited alongside, same era.
Inception-v4, inception-resnet and the impact of residual connections on learning
Szegedy, C., Ioffe, S., Vanhoucke, V.: · 2016
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Identity mappings in deep residual networks
He, K., Zhang, X., Ren, S., Sun, J.: · 2016
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Resnet in resnet: Generalizing residual architectures
Targ, S., Almeida, D., Lyman, K.: · 2016
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Deep networks with stochastic depth
Huang, G., Sun, Y., Liu, Z., Sedra, D., Weinberger, K.: · 2016
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Deep networks with stochastic depth
Sergey Zagoruyko, N.K.: · 2016
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Training very deep networks
Srivastava, R.K., Greff, K., Schmidhuber, J.: · 2015
Cited alongside, same era.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
He, K., Zhang, X., Ren, S., Sun, J.: · 2015
Cited alongside, same era.
Closest in time.
Deep residual networks with exponential linear unit
Shah, A., Kadam, E., Shah, H., Shinde, S.: · 2016
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