Huang Li

Wuhan University of Science and Technology

Papers

Total Citations

H-Index

About

Huang Li is a researcher specializing in computer vision and robotics, with a focus on instance segmentation and deep learning architectures. Their most cited work introduces an end-to-end instance segmentation method that enhances the efficiency of indoor mobile robots in locating and segmenting environmental objects. By integrating the powerful ConvNeXt V2 as the backbone network of the RTMDet model, Li significantly improves segmentation performance, addressing critical challenges in autonomous navigation and scene understanding. This contribution, published in 2024, has already garnered 2 citations, reflecting its early impact in the field. Li’s work bridges the gap between advanced neural network design and practical robotic applications, offering a robust solution for real-time environmental perception. Their research is particularly valuable for students and engineers developing autonomous systems, as it demonstrates how state-of-the-art architectures can be adapted for efficient, real-world deployment. With a clear focus on improving model performance without compromising speed, Huang Li is making notable strides in advancing the capabilities of intelligent robots.