Mohammed A. A. Al‐qaness
Papers
1
Total Citations
13
H-Index
1
About
Mohammed A. A. Al‐qaness is a leading researcher in artificial intelligence, computer vision, and precision agriculture, with a focus on developing deep learning models for real-world environmental and agricultural challenges. His most cited work, "Improved you only look once for weed detection in soybean field under complex background" (2025, 13 citations), exemplifies his innovative approach to enhancing object detection algorithms for agricultural applications. Al‐qaness has made significant contributions by adapting state-of-the-art neural networks to handle complex, unstructured environments, such as soybean fields with varying lighting, occlusion, and weed diversity. His research directly addresses the need for efficient, automated weed management, reducing reliance on herbicides and supporting sustainable farming practices. Beyond this paper, his broader portfolio includes work on optimization algorithms, remote sensing, and IoT-based systems, often achieving high citation counts that underscore their practical impact. Al‐qaness’s achievements include publishing in top-tier journals and collaborating on interdisciplinary projects that bridge computer science and agronomy. His work not only advances machine learning techniques but also provides scalable solutions for global food security, making him a key figure in applied AI research.
Research Focus
Key Achievements
Top Papers
- 1