Chien-Yao Wang

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; #3,158 of 21,575 by trust here, #2,587 by citations
• Artificial Intelligence — 215 citations into it; #12,741 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; #780 of 3,265 by trust here, #1,355 by citations
• Electrical and Electronic Engineering — 14 citations into it; #1,912 of 16,539 by trust here, #3,664 by citations
• Aerospace Engineering — 12 citations into it; #2,358 of 6,421 by trust here, #2,367 by citations

Whom Chien-Yao Wang 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. X. Zhang
7. Karen Simonyan
8. Joseph Redmon
9. Shaoqing Ren
10. Yoshua Bengio

Who trusts Chien-Yao Wang overall

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

Papers from Chien-Yao Wang's perspective

Ordered by how strongly the researchers Chien-Yao Wang 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
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