Ioannis Naounoulis
Papers
1
Total Citations
2
H-Index
1
About
Ioannis Naounoulis is a researcher at the forefront of precision agriculture and artificial intelligence, specializing in the fusion of multispectral imaging and deep learning for plant disease detection. His most cited work introduces a groundbreaking framework that integrates a dual-head SegFormer architecture with YOLO-derived segmentation masks, achieving over 11% improvement in leaf segmentation IoU. By fusing 15-channel multispectral and depth data, Naounoulis significantly enhances pixel-level classification accuracy for detecting downy mildew and gray mold in grapevines—two of the most devastating pathogens in viticulture. His research demonstrates robust performance across challenging field conditions, directly supporting deployment on UAVs and robotic platforms for real-time, automated crop monitoring. Though early in his career, with 2 citations on this flagship 2026 paper, Naounoulis’s work is already shaping the next generation of smart farming tools. His contributions bridge the gap between computer vision and sustainable agriculture, offering scalable solutions that reduce reliance on chemical fungicides while improving yield prediction and disease management.
Research Focus
Key Achievements
Top Papers
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