Caitlin Lustig
Computer Vision and Pattern Recognition · 2020
A researcher in the Science corpus: 1 paper; trusts 48 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 34 citations into it; #18,978 of 21,575 by trust here, #14,478 by citations
- Safety, Robustness & Interpretability — 20 citations into it
- Artificial Intelligence — 10 citations into it
- Evaluation & Benchmarks — 10 citations into it
- Cognitive Neuroscience — 9 citations into it; #8,788 of 10,852 by trust here, #6,723 by citations
- Signal Processing — 6 citations into it
Whom Caitlin Lustig trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Peter N. Belhumeur
- Wilma A. Bainbridge
- Joy Buolamwini
- Faisal Kamiran
- Aditya Khosla
- Karl Ricanek Jr.
- Narayanan Ramanathan
- Mahmoud Afifi
Who trusts Caitlin Lustig overall
Papers from Caitlin Lustig's perspective
Ordered by how strongly the researchers Caitlin Lustig 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Attention is All you Need (Neural Information Processing Systems)