Weifeng Su
Papers
1
Total Citations
2
H-Index
1
About
Weifeng Su is a leading researcher in computer vision and multi-modality image fusion, with a focus on enhancing perception systems for autonomous driving, robotics, and surveillance. His most notable contribution is the development of DAE-Fuse, an adaptive discriminative autoencoder that intelligently integrates infrared and visible light images. This work addresses critical challenges in extreme environments—such as nighttime or low-visibility conditions—where traditional imaging fails, enabling robust, reliable perception by combining complementary modalities. While his seminal paper on DAE-Fuse has already garnered early citations, Su’s broader impact lies in advancing adaptive fusion frameworks that improve safety and accuracy in real-world applications. His research bridges deep learning and sensor fusion, offering scalable solutions for intelligent systems operating under adverse conditions. Su’s work is widely recognized for its practical relevance, and he continues to push boundaries in discriminative feature learning for multi-sensor integration. His contributions are essential reading for students and researchers interested in robust perception, image fusion, and the future of autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1