Seunghyun Jeon

Computer Vision and Pattern Recognition · 2018

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

Subfields

• Computer Vision and Pattern Recognition — 10 citations into it

Whom Seunghyun Jeon trusts overall

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

1. Ross B. Girshick
2. Zikun Liu

Papers from Seunghyun Jeon's perspective

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

1. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
2. Fast R-CNN
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Going deeper with convolutions
6. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. ImageNet: A large-scale hierarchical image database
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• RBox-CNN: rotated bounding box based CNN for ship detection in remote sensing image (2018) — 29 citations