Scott Workman
Computer Vision and Pattern Recognition · 2015–2016
A researcher in the Science corpus: 2 papers; trusts 165 researchers and is trusted by 17 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 37 citations into it; #6,200 of 21,575 by trust here, #11,950 by citations
- Artificial Intelligence — 12 citations into it
- Media Technology — 9 citations into it; #943 of 3,621 by trust here, #1,923 by citations
- Model Architectures — 6 citations into it
Whom Scott Workman trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tsung-Yi Lin
- Alex Krizhevsky
- Geoffrey E. Hinton
- Karen Simonyan
- Diederik P. Kingma
- Hal Daumé Iii
- Andrew Zisserman
- Yoshua Bengio
- Kaiming He
- Ross B. Girshick
Who trusts Scott Workman overall
- Nam N. Vo
- Liu Liu
- Zhedong Zheng
- Yicong Tian
- Sixing Hu
- Tobias Weyand
- James Hays
- Hongdong Li
- Menghua Zhai
- Tingyu Wang
Papers from Scott Workman's perspective
Ordered by how strongly the researchers Scott Workman trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Wide-Area Image Geolocalization with Aerial Reference Imagery (2015) — 462 citations
- Predicting Ground-Level Scene Layout from Aerial Imagery (2016) — 282 citations