Kumar Abhishek

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 181 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kumar Abhishek trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Alex Krizhevsky
  4. Yann LeCun
  5. Yoshua Bengio
  6. Ross B. Girshick
  7. Karen Simonyan
  8. Ilya Sutskever
  9. Diederik P. Kingma
  10. Andrew Zisserman

Papers from Kumar Abhishek's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Gradient-based learning applied to document recognition
  4. Long Short-Term Memory
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. ImageNet: A large-scale hierarchical image database
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Going deeper with convolutions
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers