Teng Xi

Computer Vision and Pattern Recognition · 2020–2023

A researcher in the Science corpus: 2 papers; trusts 26 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 58 citations into it
• Artificial Intelligence — 46 citations into it

Whom Teng Xi trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Yann LeCun
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Diederik P. Kingma
7. Ross B. Girshick
8. Ilya Sutskever
9. Karen Simonyan
10. Christian Szegedy

Papers from Teng Xi's perspective

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

Their papers

• AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results (2020) — 43 citations
• A Unified Continual Learning Framework with General Parameter-Efficient Tuning (2023) — 161 citations