Gabriel Humpire-Mamani

Computer Vision and Pattern Recognition · 2012

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Gabriel Humpire-Mamani trusts overall

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

  1. Manik Varma
  2. Svetlana Lazebnik
  3. Barbara Caputo
  4. Robert Martin Haralick
  5. Ping-Sung Liao
  6. Andrew Zisserman
  7. Timo Ahonen
  8. Ritendra Datta
  9. Cordelia Schmid

Papers from Gabriel Humpire-Mamani's perspective

Ordered by how strongly the researchers Gabriel Humpire-Mamani 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. ImageNet: A large-scale hierarchical image database
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. ImageNet Large Scale Visual Recognition Challenge
  7. Learning Multiple Layers of Features from Tiny Images
  8. Going deeper with convolutions
  9. Long Short-Term Memory
  10. Distinctive Image Features from Scale-Invariant Keypoints

Their papers