Wei Ke

Computer Vision and Pattern Recognition · with Chen · 2017–2021

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it
• Artificial Intelligence — 26 citations into it
• Representation & Self-Supervised Learning — 10 citations into it

Whom Wei Ke trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton

Papers from Wei Ke's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Learning Multiple Layers of Features from Tiny Images
3. Distilling the Knowledge in a Neural Network (arXiv.org)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Fully convolutional networks for semantic segmentation
6. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
7. ImageNet: A large-scale hierarchical image database
8. Gradient-based learning applied to document recognition
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Class-Incremental Learning with Topological Schemas of Memory Spaces (2021) — 5 citations
• A location-to-segmentation strategy for automatic exudate segmentation in colour retinal fundus images (2017) — 91 citations