Jonathan Ventura

Computer Vision and Pattern Recognition · with Boult · 2020

A researcher in the Science corpus: 1 paper; trusts 140 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 24 citations into it
• Artificial Intelligence — 16 citations into it

Whom Jonathan Ventura trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Tsung-Yi Lin
4. Shaoqing Ren
5. Joseph Redmon
6. Alex Krizhevsky
7. Geoffrey E. Hinton
8. Pedro F. Felzenszwalb
9. Yann LeCun
10. Andrew Zisserman

Papers from Jonathan Ventura's perspective

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

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

Their papers

• The Overlooked Elephant of Object Detection: Open Set (2020) — 199 citations