En Li

Computer Vision and Pattern Recognition · with Liang · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 26 citations into it
• Model Architectures — 7 citations into it

Whom En Li trusts overall

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

1. Joseph Redmon
2. Kaiming He
3. Karen Simonyan
4. Christian Szegedy

Who trusts En Li overall

1. Diana-Margarita Córdova-Esparza
2. Juan R. Terven

Papers from En Li's perspective

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

Their papers

• A Review on State-of-the-Art Power Line Inspection Techniques (2020) — 342 citations
• Apple detection during different growth stages in orchards using the improved YOLO-V3 model (2019) — 963 citations