Elanchezhian Arulmozhi
Papers
3
Total Citations
46
H-Index
3
About
Elanchezhian Arulmozhi is at the forefront of agricultural artificial intelligence, specializing in deep learning, computer vision, and digital twin technology for smart farming. His research addresses critical challenges in food security by developing intelligent systems for precision agriculture and automated harvesting. Arulmozhi’s most influential work, "From Reality to Virtuality: Revolutionizing Livestock Farming Through Digital Twins" (2024, 24 citations), pioneers the integration of virtual replicas into livestock management to combat climate-induced production losses. He has also made significant contributions to robotic fruit harvesting, creating lightweight detection algorithms like the improved YOLOv5s-CGhostnet for strawberry maturity assessment (15 citations) and the DF-Mask R-CNN framework for peduncle detection and picking-point localization (7 citations). These innovations enable harvesting robots to operate with high accuracy while minimizing fruit damage. With a growing citation record and publications in top venues, Arulmozhi is shaping the future of autonomous agriculture—bridging the gap between virtual simulation and real-world farming efficiency.
Research Focus
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Top Papers
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