L. Zhang

Computer Vision and Pattern Recognition · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2016–2022

A researcher in the Science corpus: 7 papers; trusts 554 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 238 citations into it; #9,483 of 21,575 by trust here, #8,122 by citations
• Artificial Intelligence — 125 citations into it; #16,240 of 35,345 by trust here, #14,718 by citations
• Media Technology — 54 citations into it
• Multimodal Learning — 45 citations into it; #570 of 1,211 by trust here, #862 by citations
• Natural Language Processing — 25 citations into it
• Model Architectures — 20 citations into it
• Representation & Self-Supervised Learning — 15 citations into it

Whom L. Zhang trusts overall

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

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

Who trusts L. Zhang overall

1. Jianfeng Wang
2. Xiaowei Hu
3. Gong Cheng

Papers from L. Zhang's perspective

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

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

Their papers

• VIVO: Surpassing Human Performance in Novel Object Captioning with Visual Vocabulary Pre-Training (2020) — 58 citations
• MiniVLM: A Smaller and Faster Vision-Language Model (2020) — 76 citations
• Advancing Plain Vision Transformer Toward Remote Sensing Foundation Model (2022) — 379 citations
• Weighted Feature Fusion of Convolutional Neural Network and Graph Attention Network for Hyperspectral Image Classification (2022) — 475 citations
• Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges (2021) — 655 citations
• WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional neural network with CRF (2020) — 523 citations
• A spectral–structural bag-of-features scene classifier for very high spatial resolution remote sensing imagery (2016) — 134 citations