Jeongyeol Choe

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 2 papers; 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 Jeongyeol Choe trusts overall

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

1. Ross B. Girshick
2. Zikun Liu

Papers from Jeongyeol Choe's perspective

Ordered by how strongly the researchers Jeongyeol Choe 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. Ship Rotated Bounding Box Space for Ship Extraction From High-Resolution Optical Satellite Images With Complex Backgrounds (IEEE Geoscience and Remote Sensing Letters)
8. DOTA: A Large-Scale Dataset for Object Detection in Aerial Images
9. Gradient-based learning applied to document recognition
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Noise-adding Methods of Saliency Map as Series of Higher Order Partial Derivative (2018) — 30 citations
• RBox-CNN: rotated bounding box based CNN for ship detection in remote sensing image (2018) — 29 citations