Chas Leichner

Computer Vision and Pattern Recognition · 2021–2025

A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Chas Leichner trusts overall

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

  1. Kaiming He
  2. Tsung-Yi Lin
  3. Christian Szegedy
  4. Alex Krizhevsky
  5. Geoffrey E. Hinton
  6. Ross B. Girshick
  7. Quoc V. Le
  8. Yoshua Bengio
  9. Yann LeCun
  10. Diederik P. Kingma

Papers from Chas Leichner's perspective

Ordered by how strongly the researchers Chas Leichner 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. Attention is All you Need (Neural Information Processing Systems)
  4. ImageNet Large Scale Visual Recognition Challenge
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. ImageNet: A large-scale hierarchical image database
  7. Long Short-Term Memory
  8. Gradient-based learning applied to document recognition
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Going deeper with convolutions

Their papers