Michal Cohen-Sfaty
Computer Vision and Pattern Recognition · 2018
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
- Computer Vision and Pattern Recognition — 9 citations into it
- Artificial Intelligence — 7 citations into it
Whom Michal Cohen-Sfaty trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Michal Cohen-Sfaty's perspective
Ordered by how strongly the researchers Michal Cohen-Sfaty trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Rethinking the Inception Architecture for Computer Vision
- Fully convolutional networks for semantic segmentation
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory