Abdulaziz Saud Altamrah
Papers
1
Total Citations
3
H-Index
1
About
Abdulaziz Saud Altamrah’s research centers on agricultural technology and intelligent image processing, with a particular focus on disease detection in crops using machine learning. His most cited work, a correction to a study on apple disease classification, highlights his commitment to precision in computational agriculture. The original paper developed an optimized method for segmentation and classification of apple diseases, leveraging strong correlation analysis and genetic algorithm-based feature selection to improve diagnostic accuracy. This contribution addresses a critical challenge in smart farming: enabling early and reliable detection of plant pathogens to reduce crop loss and pesticide use. While the correction itself has garnered 3 citations, it underscores Altamrah’s attention to methodological rigor and reproducibility—values essential to advancing applied AI in agriculture. His work sits at the intersection of computer vision, feature engineering, and agricultural science, offering practical tools for farmers and researchers. By refining how algorithms select relevant features from complex plant images, Altamrah contributes to more efficient, scalable disease monitoring systems. His research is particularly valuable for developing regions where automated, low-cost diagnostic tools can transform food security and sustainable farming practices.
Research Focus
Key Achievements
Top Papers
- 1