Yang LIU

Jiangxi University of Science and Technology

Papers

Total Citations

H-Index

About

Yang Liu is a researcher specializing in computer vision and image processing, with a particular focus on stereo matching algorithms for specialized imaging domains. His most cited work, "Stereo matching algorithm for mineral images based on improved BT-Census" (2024), introduces a novel approach that enhances the traditional BT-Census method to address the unique challenges of mineral image analysis—such as texture variability and lighting inconsistencies—achieving more accurate depth estimation. This contribution has garnered 5 citations, marking it as a foundational piece in the niche field of mineral image stereo matching. Liu’s research bridges the gap between general computer vision techniques and practical applications in geology and resource exploration, offering tools that improve automated analysis of mineral samples. His work is notable for its targeted innovation, adapting established algorithms to solve real-world problems in scientific imaging. For students and researchers, Liu’s approach demonstrates the value of domain-specific algorithm refinement, showing how even modest citation counts can signal meaningful impact in specialized fields. His ongoing efforts continue to advance the precision and efficiency of stereo matching for mineralogical and geological applications.