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About

Erhan Kahya is a rising researcher at the intersection of agricultural engineering and artificial intelligence, specializing in deep learning-driven robotic automation for specialty crop harvesting. His work focuses on developing real-time object detection systems that enable agricultural robots to identify, select, and harvest fruits and vegetables with precision. Kahya’s most cited paper, “Application of YOLOv8L Deep Learning in Robotic Harvesting of Persimmon,” demonstrates how advanced neural networks can outperform traditional methods in analyzing complex agricultural environments. He has also applied the YOLOv5 model to real-time robotic eggplant harvesting, showcasing the adaptability of his approach across different crops. In a related study on lettuce seedling selection, Kahya addressed the critical early stage of crop production, using deep learning to distinguish healthy seedlings from weak ones—a task vital for yield and quality. Though early in his career, with his top-cited work accumulating 4 citations since 2023, Kahya is contributing to a transformative shift in agriculture: replacing manual labor with intelligent, vision-guided robotic systems. His research promises to reduce labor costs, increase efficiency, and support sustainable farming practices, positioning him as a promising voice in precision agriculture and agri-robotics.