Saud Yonbawi
Papers
1
Total Citations
9
H-Index
1
About
Dr. Saud Yonbawi is a prominent researcher in artificial intelligence, precision agriculture, and computational optimization. His work focuses on integrating advanced machine learning and metaheuristic algorithms to solve critical challenges in sustainable farming and environmental monitoring. Notably, his highly cited 2023 paper, "Harris Hawks Optimizer with Graph Convolutional Network Based Weed Detection in Precision Agriculture," introduces a novel hybrid framework that combines the Harris Hawks optimization algorithm with graph convolutional networks for accurate, real-time weed identification. This contribution directly addresses the pressing need for resource-efficient crop management, balancing agricultural productivity with ecological sustainability. With over 9 citations, this work exemplifies his impact in applying AI to optimize resource use and reduce environmental harm. Dr. Yonbawi’s research bridges theoretical optimization and practical agricultural technology, offering scalable solutions for modern farming. His achievements underscore a commitment to developing intelligent systems that enhance precision agriculture, making him a key figure in the intersection of computational intelligence and sustainable development.
Research Focus
Key Achievements
Top Papers
- 1