R. Mlambo

Environmental Engineering · 2017

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom R. Mlambo trusts overall

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

  1. David G. Lowe
  2. Changchang Wu
  3. Yasutaka Furukawa
  4. Michal Jancosek
  5. Noah Snavely
  6. Jean Ponce
  7. Tomás Pajdla
  8. S. M. Seitz
  9. Richard Szeliski

Papers from R. Mlambo's perspective

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

  1. Distinctive Image Features from Scale-Invariant Keypoints
  2. Object recognition from local scale-invariant features
  3. Modeling the World from Internet Photo Collections (International Journal of Computer Vision)
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Gradient-based learning applied to document recognition
  6. ImageNet classification with deep convolutional neural networks
  7. ImageNet: A large-scale hierarchical image database
  8. Going deeper with convolutions
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Accurate, Dense, and Robust Multi-View Stereopsis

Their papers