Joshua Kravitz

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 2 papers; trusts 105 researchers and is trusted by 657 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 88 citations into it; #1,665 of 21,575 by trust here, #959 by citations
• Evaluation & Benchmarks — 27 citations into it; #787 of 3,147 by trust here, #138 by citations

Whom Joshua Kravitz trusts overall

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

1. Jia Deng
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Andrew Zisserman
5. Karen Simonyan
6. Ross B. Girshick
7. Li Fei-Fei
8. Yoshua Bengio
9. Kaiming He
10. Ilya Sutskever

Who trusts Joshua Kravitz overall

1. Ronghang Hu
2. Zhe Gan
3. Marcella Cornia
4. Zhou Yu
5. Damien Teney
6. Jiasen Lu
7. Xinlei Chen
8. Tianfu Wu
9. Kushal Kafle
10. Mohit Bansal

Papers from Joshua Kravitz's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. ImageNet: A large-scale hierarchical image database
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. ImageNet Large Scale Visual Recognition Challenge
6. Going deeper with convolutions
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Attention is All you Need (Neural Information Processing Systems)
10. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Their papers

• Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations (2016) — 6,638 citations
• Embracing Error to Enable Rapid Crowdsourcing (2016) — 93 citations