James Akl

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom James Akl trusts overall

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

  1. Kaiming He
  2. Ross B. Girshick

Papers from James Akl's perspective

Ordered by how strongly the researchers James Akl 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. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  4. Microsoft COCO: Common Objects in Context
  5. ImageNet: A large-scale hierarchical image database
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Long Short-Term Memory

Their papers