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2 papers

2014Advances in Neural Information Processing Systems (NeurIPS) 2014, pp. 3320-3328

How transferable are features in deep neural networks?

Jason Yosinski, Yoshua Bengio, Jeff Clune, Hod Lipson

Finding: They found that features become increasingly specific to the original task in higher layers, but still transfer well to related tasks. Transferability degrades as the divergence between tasks increases.

transfer learning feature extraction

2012Advances in Neural Information Processing Systems (NeurIPS) 2012, pp. 1097-1105

ImageNet Classification with Deep Convolutional Neural Networks

Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever

Finding: AlexNet won the ImageNet 2012 competition by a large margin (15.3% top-5 error vs 26.2% for the second best), proving that deep CNNs are highly effective on large-scale data.

CNN ImageNet