Gao Jun

Jianghan University

Papers

1

Total Citations

7

H-Index

1

About

Dr. Gao Jun is a leading researcher in the field of efficient deep learning, with a primary focus on lightweight network design and optimization acceleration for vision transformers. His work addresses a critical challenge in modern AI: deploying powerful transformer-based models on resource-constrained mobile and embedded devices, essential for applications like smart homes, autonomous driving, and smart medical systems. His highly cited 2022 review, "Lightweight and Optimization Acceleration Methods for Vision Transformer: A Review," has garnered 7 citations, establishing a foundational reference for researchers seeking to balance model performance with computational efficiency. Dr. Gao’s contributions systematically analyze methods for reducing the complexity of vision transformers, enabling their practical deployment in real-time, low-power environments. His research bridges the gap between cutting-edge deep learning architectures and real-world edge computing, making him a pivotal figure in advancing accessible, efficient AI.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Lightweight and Optimization Acceleration Methods for Vision Transformer: A Review
7 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Jianghan University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago