Anju Rani
Papers
2
Total Citations
5
H-Index
2
About
Anju Rani is an emerging researcher whose work sits at the intersection of computer vision, deep learning, and industrial systems, with a particular focus on 3D point cloud analysis and its real-world applications. Her research addresses the growing demand for automated defect detection and classification in industrial environments, leveraging cutting-edge deep learning techniques to extract meaningful insights from complex three-dimensional data. Her most notable contribution is a comprehensive survey on point cloud-based 3D defect detection and classification for industrial systems, published in 2024, which has already begun attracting attention from the research community with citations accumulating across its iterations. This work systematically examines advancements in processing 3D point clouds for condition monitoring, robotics, autonomous driving, virtual reality, and broader computer vision applications — making it a valuable reference for researchers navigating this rapidly evolving field. By synthesizing the state of deep learning applied to 3D point clouds, Rani's survey serves as an accessible yet thorough roadmap for both newcomers and established researchers seeking to understand where the field stands and where it is headed. Her contributions reflect a commitment to bridging foundational methodology with practical industrial impact.
Research Focus
Key Achievements
Top Papers
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- 2