Hongpeng Liao

Computer Vision and Pattern Recognition · 2019–2024

A researcher in the Science corpus: 7 papers; trusts 1,608 researchers and is trusted by 96 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 331 citations into it; #3,157 of 21,575 by trust here, #2,587 by citations
• Artificial Intelligence — 215 citations into it; #12,740 of 35,345 by trust here, #10,207 by citations
• Model Architectures — 92 citations into it
• Efficiency & Compression — 40 citations into it
• Optimization & Training — 26 citations into it
• Radiology, Nuclear Medicine and Imaging — 25 citations into it; #779 of 3,265 by trust here, #1,355 by citations
• Electrical and Electronic Engineering — 14 citations into it; #1,911 of 16,539 by trust here, #3,664 by citations
• Aerospace Engineering — 12 citations into it; #2,357 of 6,421 by trust here, #2,367 by citations

Whom Hongpeng Liao trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Christian Szegedy
6. Yoshua Bengio
7. Karen Simonyan
8. X. Zhang
9. Yann LeCun
10. Shaoqing Ren

Who trusts Hongpeng Liao overall

1. Chien-Yao Wang
2. Juan R. Terven
3. Hulin Li
4. Ao Wang
5. Diganta Misra
6. I-Hau Yeh
7. Diana-Margarita Córdova-Esparza
8. Muhammad Hussain
9. Xingkui Zhu
10. Ming Kang

Papers from Hongpeng Liao's perspective

Ordered by how strongly the researchers Hongpeng Liao 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: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• YOLOv4: Optimal Speed and Accuracy of Object Detection (2020) — 15,853 citations
• Scaled-YOLOv4: Scaling Cross Stage Partial Network (2020) — 1,445 citations
• YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors (2022) — 10,740 citations
• CSPNet: A New Backbone that can Enhance Learning Capability of CNN (2019) — 4,207 citations
• YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information (2024) — 4,085 citations
• Designing Network Design Strategies Through Gradient Path Analysis (2022) — 377 citations
• You Only Learn One Representation: Unified Network for Multiple Tasks (2021) — 596 citations