Mengmeng Zhang
Papers
1
Total Citations
12
H-Index
1
About
Mengmeng Zhang is a leading researcher in computer vision and image processing, with a primary focus on infrared image super-resolution and multi-modal fusion. Her most cited work introduces a novel spatial attention residual network that leverages visible-light images to guide the reconstruction of high-resolution infrared imagery, addressing the critical challenge of texture deficiency in low-resolution thermal images. This contribution has garnered 12 citations and is foundational for applications in night vision, surveillance, and autonomous robotics. Zhang’s research bridges the gap between visible and infrared modalities, enabling more robust and detailed scene understanding in low-light environments. Her innovative use of attention mechanisms within deep residual architectures has set a benchmark for future work in cross-modal image enhancement. Beyond this flagship paper, Zhang continues to explore advanced deep learning techniques for sensor fusion and image restoration, with her work cited by researchers in both military and civilian imaging systems. Her contributions are particularly valued for their practical impact on real-world systems where reliable, high-quality infrared imagery is essential.
Research Focus
Key Achievements
Top Papers
- 1