Yasin Aslan

Papers

Total Citations

H-Index

About

Yasin Aslan is an emerging researcher at the intersection of deep learning and agricultural automation, with a particular focus on real-time robotic harvesting systems. His most-cited work, "YOLOv5 Model Application in Real-Time Robotic Eggplant Harvesting" (2024), demonstrates a practical application of computer vision to address critical challenges in modern agriculture—improving crop yield efficiency while reducing reliance on manual labor. By integrating the YOLOv5 object detection model into a robotic harvesting framework, Aslan contributes to the growing field of precision agriculture, where AI-driven automation promises to transform food production. Although his citation count is still building, this work reflects a timely and impactful contribution to deep learning-based agricultural robotics. Aslan’s research aligns with broader trends in smart farming, disease identification, and yield estimation, positioning him as a promising voice in the application of artificial intelligence to real-world agricultural problems. His work is especially relevant for students and researchers interested in the convergence of computer vision, robotics, and sustainable food systems.