Kireet Muppavaram

Papers

Total Citations

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About

Kireet Muppavaram is a researcher at the intersection of computer vision, dental healthcare, and privacy-preserving imaging technologies. His work focuses on applying deep learning to improve oral health diagnostics, particularly through automated detection systems. Muppavaram’s most cited paper, “Mask RCNN with RESNET50 for Dental Filling Detection” (2021, 5 citations), introduces a novel approach to identifying dental fillings using convolutional neural networks, addressing the critical need for efficient tools amid a global shortage of dentists. He extended this work in “Advancements in Dental Filling Detection Technologies and Strategies for Comprehensive Oral Health Care” (2024, 4 citations), which synthesizes emerging strategies for integrating AI into routine dental practice. Beyond dentistry, Muppavaram has explored omnidirectional vision systems in “Investigation of Omnidirectional Vision and Privacy Protection in Omnidirectional Cameras” (2023, 2 citations), examining how 360-degree imaging can be deployed responsibly in telecommunications, robotics, and multimedia. His research demonstrates a commitment to leveraging AI for practical, real-world impact—from improving patient outcomes in oral care to ensuring privacy in advanced imaging. With a growing citation footprint, Muppavaram’s work is paving the way for smarter, more accessible healthcare technologies.