R. McBride

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom R. McBride trusts

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

  1. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  2. Kaiming He (in Computer Vision and Pattern Recognition)
  3. Shaoqing Ren (in Computer Vision and Pattern Recognition)

Papers from R. McBride's perspective

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

  1. ImageNet Large Scale Visual Recognition Challenge
  2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  3. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  4. A Fast Learning Algorithm for Deep Belief Nets
  5. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
  6. Fast R-CNN
  7. ImageNet classification with deep convolutional neural networks
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Gradient-based learning applied to document recognition
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers