Varun Gulshan
Computer Vision and Pattern Recognition · 2009–2017
A researcher in the Science corpus: 4 papers; trusts 207 researchers and is trusted by 1,395 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 43 citations into it; #1,106 of 21,575 by trust here, #3,848 by citations
- Artificial Intelligence — 22 citations into it; #5,017 of 35,345 by trust here, #6,664 by citations
- Evaluation & Benchmarks — 7 citations into it
Whom Varun Gulshan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- Andrew Zisserman
- Carsten Rother
- Jianguo Zhang
- Andrea Vedaldi
- Olga Veksler
- Christian Szegedy
- Yuri Boykov
- Geoffrey E. Hinton
- Yann LeCun
Who trusts Varun Gulshan overall
- Wanli Ouyang
- Andrea Vedaldi
- Jasper R. R. Uijlings
- Xiaogang Wang
- Jia Deng
- Liang-Chieh Chen
- Vittorio Ferrari
- Andrew Zisserman
- Xiaodan Liang
- Kristen Grauman
Papers from Varun Gulshan's perspective
Ordered by how strongly the researchers Varun Gulshan 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
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Multiple kernels for object detection (2009) — 868 citations
- Geodesic star convexity for interactive image segmentation (2010) — 448 citations
- Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy (2017) — 503 citations
- Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. (2016) — 6,915 citations