Santosh Madeva Naik

Papers

Total Citations

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About

Santosh Madeva Naik is an emerging researcher in the field of computer vision and environmental sustainability, with a primary focus on applying deep learning to underwater pollution detection. His most cited work, "Octacleaner: Underwater Trash Detection Through YOLO" (2023), addresses the critical problem of underwater waste management by leveraging the YOLO object detection algorithm to identify submerged debris such as plastics, metals, and glass. This contribution is particularly significant given the global challenge of inadequate waste management, where millions of tons of trash wash into water bodies daily, threatening aquatic ecosystems. With 5 citations, this paper has already garnered attention for its practical approach to automating trash detection, a step toward scalable cleanup solutions. Naik’s research bridges artificial intelligence and environmental engineering, offering a cost-effective method to monitor and mitigate underwater pollution. His work stands out for its real-world applicability, aiming to reduce the reliance on manual cleanup efforts. As a researcher, Naik is contributing to the growing intersection of AI and ecological conservation, making his findings valuable for students and scientists interested in sustainable technology and marine preservation.