Rashmita Khilar

Papers

Total Citations

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About

Rashmita Khilar is a researcher whose work spans 3D image reconstruction, object classification, and AI-driven cybersecurity. Her most cited paper, "3D image reconstruction: Techniques, applications and challenges" (2013, 24 citations), tackles the fundamental inverse problem of recovering ideal images from degraded versions—whether corrupted by noise, blur, or damage—and explores how reconstruction techniques create three-dimensional representations. This foundational contribution has informed advances in medical imaging, remote sensing, and computer vision. In "Colour based Object Classification using KNN Algorithm for Industrial Applications" (2022, 5 citations), Khilar addresses practical challenges in automated sorting and quality control, leveraging color properties for robust classification in manufacturing environments. Her work "Artificial intelligence based optimization for mapping IP addresses to prevent cyber-based attacks" (2022, 4 citations) applies AI to enhance decision-making in network security, reflecting a growing interest in intelligent defense systems. Across these domains, Khilar demonstrates a commitment to solving real-world problems—from restoring visual data to securing digital infrastructure—making her contributions valuable for students and researchers exploring the intersection of image processing, machine learning, and cybersecurity.