Yong Guo

Computer Vision and Pattern Recognition · with Chen · 2005–2021

A researcher in the Science corpus: 14 papers; trusts 1,061 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 412 citations into it; #8,102 of 21,575 by trust here, #5,116 by citations
• Artificial Intelligence — 231 citations into it; #21,537 of 35,345 by trust here, #9,092 by citations
• Model Architectures — 91 citations into it
• Efficiency & Compression — 78 citations into it
• Media Technology — 73 citations into it
• Generative Models — 69 citations into it
• Optimization & Training — 55 citations into it
• Signal Processing — 34 citations into it

Whom Yong Guo trusts overall

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

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

Who trusts Yong Guo overall

1. Jian Chen
2. Mingkui Tan
3. Jing Liu
4. Yongsheng Luo
5. Jingdong Wang
6. Qi Chen
7. Bohan Zhuang
8. Runhao Zeng
9. Jiezhang Cao
10. Zhuangwei Zhuang

Papers from Yong Guo's perspective

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

Their papers

• Discrimination-aware Channel Pruning for Deep Neural Networks (2018) — 637 citations
• NAT: Neural Architecture Transformer for Accurate and Compact Architectures (2019) — 101 citations
• Adversarial Learning with Local Coordinate Coding (2018) — 39 citations
• Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search (2020) — 78 citations
• N-doped porous carbon nanofibers sheathed pumpkin-like Si/C composites as free-standing anodes for lithium-ion batteries (2021) — 182 citations
• Discrimination-Aware Network Pruning for Deep Model Compression (2020) — 169 citations
• Hierarchical Neural Architecture Search for Single Image Super-Resolution (2020) — 53 citations
• Closed-Loop Matters: Dual Regression Networks for Single Image Super-Resolution (2020) — 319 citations
• Auto-Embedding Generative Adversarial Networks For High Resolution Image Synthesis (2019) — 69 citations
• Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss (2018) — 17 citations
• Double Forward Propagation for Memorized Batch Normalization (2018) — 29 citations
• The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary Outputs (2016) — 13 citations
• Effect of octadeca carbon fatty acids on microbial fermentation, methanogenesis and microbial flora in vitro (2008) — 142 citations
• A new wide-band planar balun on a single-layer PCB (2005) — 181 citations