R. Logeshwari

Papers

Total Citations

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About

R. Logeshwari is a researcher in applied computer vision and intelligent quality control systems, with a focus on automating defect detection in industrial and manufacturing contexts. Her most-cited work, "Scratch Detection in Cars Using Mask Region Convolution Neural Networks" (2020, 10 citations), introduces a deep learning framework for identifying cosmetic imperfections—such as scratches and dents—on new vehicles before delivery. By leveraging Mask R-CNN, she developed a robust, automated system that enhances traditional manual inspection, improving both speed and accuracy in automotive quality assurance. This contribution addresses a critical bottleneck in production lines, reducing human error and ensuring higher standards of finish for end customers. Her research sits at the intersection of computer vision, neural networks, and industrial automation, demonstrating how AI can streamline real-world manufacturing processes. With growing interest in smart quality control, Logeshwari’s work lays a foundation for scalable, robot-assisted inspection systems. Her achievements highlight the practical impact of deep learning in non-medical imaging domains, offering a compelling model for students and researchers exploring defect detection in complex, real-world environments.