Ming Kang

Computer Vision and Pattern Recognition · with Ting · 2023

A researcher in the Science corpus: 1 paper; trusts 163 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 23 citations into it
• Artificial Intelligence — 14 citations into it

Whom Ming Kang trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Chien-Yao Wang
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Tsung-Yi Lin
7. Piotr Doll'ar
8. Yann LeCun
9. Karen Simonyan
10. Yoshua Bengio

Papers from Ming Kang's perspective

Ordered by how strongly the researchers Ming Kang 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 classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation (2023) — 445 citations