Debdeep Paul

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Debdeep Paul trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Surat Teerapittayanon
  2. Bradley McDanel
  3. Alex Krizhevsky

Who trusts Debdeep Paul overall

  1. Yizeng Han
  2. Gao Huang
  3. Canwen Xu

Papers from Debdeep Paul's perspective

Ordered by how strongly the researchers Debdeep Paul trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Going deeper with convolutions
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Gradient-based learning applied to document recognition
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Long Short-Term Memory
  9. Learning Multiple Layers of Features from Tiny Images
  10. Dropout: a simple way to prevent neural networks from overfitting

Their papers