Papers
1
Total Citations
13
H-Index
1
About
Linlin Zhu is a researcher specializing in computer vision and underwater image analysis, with a particular focus on enhancing target detection in challenging marine environments. Her most-cited work, "Underwater Target Detection Based on Parallel High-Resolution Networks" (2023), has garnered 13 citations and introduces a novel approach that leverages a parallel high-resolution network (HRNet) to overcome the limitations of complex underwater scenes and weak feature extraction. By adapting a lightweight human posture estimation network for underwater contexts, Zhu’s method significantly improves detection accuracy and robustness, addressing critical gaps in autonomous underwater vehicle navigation and marine surveillance. Her contributions are notable for bridging high-resolution network architectures with domain-specific challenges, offering a scalable solution for real-time object recognition in low-visibility conditions. Zhu’s work holds promise for advancing underwater robotics and environmental monitoring, reflecting her dedication to practical, high-impact computer vision applications.
Research Focus
Key Achievements
Top Papers
- 1Underwater Target Detection Based on Parallel High-Resolution Networks13 citations · 2023