Harsh Agrawal

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 8 papers; trusts 800 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

Whom Harsh Agrawal trusts overall

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

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

Who trusts Harsh Agrawal overall

  1. Xiaowei Hu
  2. Jiasen Lu
  3. Jianfeng Wang
  4. Marcella Cornia
  5. Junnan Li
  6. Pengchuan Zhang
  7. Chen Sun
  8. Wenliang Dai
  9. Zhe Gan
  10. Amita Kamath

Papers from Harsh Agrawal's perspective

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

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

Their papers