Peter Anthony Beerel

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 39 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 31 citations into it
• Artificial Intelligence — 20 citations into it
• Model Architectures — 6 citations into it

Whom Peter Anthony Beerel trusts overall

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

1. Alex Krizhevsky
2. Christian Szegedy
3. Kaiming He
4. Karen Simonyan

Papers from Peter Anthony Beerel's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Going deeper with convolutions
4. Learning Multiple Layers of Features from Tiny Images
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
7. Gradient-based learning applied to document recognition
8. Rethinking the Inception Architecture for Computer Vision
9. ImageNet Large Scale Visual Recognition Challenge
10. Long Short-Term Memory

Their papers

• Pre-Defined Sparsity for Low-Complexity Convolutional Neural Networks (2020) — 37 citations