Zulkalnain Mohd Yussof

Technical University of Malaysia Malacca

Papers

Total Citations

H-Index

About

Zulkalnain Mohd Yussof is a researcher whose work sits at the intersection of computer vision, deep learning, and agricultural robotics. His primary research focuses on developing intelligent vision systems that can identify and classify crops and their parts—such as chili plants and their flowers—to enable automated harvesting. His most cited paper, "Classification and detection of chili and its flower using deep learning approach" (2020, 13 citations), introduces a Deep Neural Network (DNN)-based detector tailored for a single local chili variety, laying essential groundwork for robotic picking systems in precision agriculture. This contribution is particularly significant for small-scale and tropical farming, where automation can reduce labor dependency and improve yield efficiency. Beyond this flagship work, Yussof’s research spans object detection and classification in agricultural contexts, often emphasizing practical, low-cost solutions. While his citation count is still growing, his work has already informed subsequent studies in agricultural robotics and plant phenotyping. By bridging deep learning with real-world farming challenges, Yussof is helping to shape the next generation of autonomous agricultural tools—making his research both technically sound and socially impactful for students and engineers interested in AI-driven agritech.