Assia Naja

Technical University of Malaysia Malacca

Papers

Total Citations

H-Index

About

Assia Naja is a leading researcher at the intersection of artificial intelligence and precision agriculture, with a primary focus on deep learning applications for robotic vision in crop management. Her most-cited work, "Disease Detection of Solanaceous Crops Using Deep Learning for Robot Vision" (2022, 20 citations), addresses a critical challenge in modern farming: the labor-intensive and error-prone process of manually identifying plant diseases. Naja’s major contribution lies in developing automated, vision-based systems that enable robots to detect diseases, nutrient deficiencies, and irrigation needs in solanaceous crops—such as tomatoes and potatoes—with high accuracy. This innovation reduces reliance on human expertise and minimizes the overuse of fertilizers and pesticides, promoting sustainable agriculture. Beyond her flagship paper, Naja’s research portfolio spans sensor fusion, machine learning for environmental monitoring, and smart farming frameworks. Her work has garnered attention for its practical impact, bridging the gap between cutting-edge AI and real-world agricultural challenges. For students and researchers, Naja exemplifies how deep learning can transform traditional industries, offering a compelling model for applying computer vision to solve pressing global food security issues.