Benjamin Koger

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 29 citations into it

Whom Benjamin Koger trusts

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

1. Shaoqing Ren (in Computer Vision and Pattern Recognition)
2. Kaiming He (in Computer Vision and Pattern Recognition)
3. Ross B. Girshick (in Computer Vision and Pattern Recognition)
4. Jia Deng (in Computer Vision and Pattern Recognition)
5. X. Zhang (in Computer Vision and Pattern Recognition)

Papers from Benjamin Koger's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet: A large-scale hierarchical image database
3. GENERATIVE ADVERSARIAL NETS
4. Fully convolutional networks for semantic segmentation
5. ImageNet classification with deep convolutional neural networks
6. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
7. Gradient-based learning applied to document recognition
8. A Stochastic Approximation Method
9. Long Short-Term Memory
10. Going deeper with convolutions

Their papers

• DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning (2019) — 474 citations