Renlong Hang

Media Technology · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 47 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Media Technology — 75 citations into it; #2,490 of 3,621 by trust here, #941 by citations
• Atmospheric Science — 43 citations into it
• Computer Vision and Pattern Recognition — 41 citations into it; #20,394 of 21,575 by trust here, #11,721 by citations
• Artificial Intelligence — 30 citations into it
• Biomedical Engineering — 13 citations into it
• Model Architectures — 11 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Signal Processing — 8 citations into it

Whom Renlong Hang trusts overall

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

1. Geoffrey E. Hinton
2. Ilya Sutskever
3. Alex Graves
4. Yoshua Bengio
5. Yushi Chen
6. Alex Krizhevsky
7. Yann LeCun
8. J. Urgen Schmidhuber
9. Kyunghyun Cho
10. Kaiming He

Who trusts Renlong Hang overall

1. Danfeng Hong
2. Xin He
3. Lichao Mou
4. Guangrui Zhao
5. Yushi Chen
6. Swalpa Kumar Roy
7. Lin Zhu
8. Sheng Wan
9. Muhammad Ahmad
10. Qiqi Zhu

Papers from Renlong Hang's perspective

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

Their papers

• Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox (2020) — 480 citations
• Classification of Hyperspectral and LiDAR Data Using Coupled CNNs (2020) — 367 citations
• Cascaded Recurrent Neural Networks for Hyperspectral Image Classification (2017) — 680 citations