Qisong Mou
Papers
1
Total Citations
28
H-Index
1
About
Dr. Qisong Mou is a leading researcher in agricultural artificial intelligence and computer vision, with a primary focus on precision agriculture and automated crop disease detection. His most influential work, "Research on Detection Technology of Various Fruit Disease Spots Based on Mask R-CNN" (2020), has garnered 28 citations and represents a significant breakthrough in agricultural quality control. In this seminal paper, Dr. Mou addresses critical limitations in traditional fruit disease detection—namely low accuracy, slow processing speeds, and the labor-intensive nature of manual quality classification. By developing a Mask R-CNN-based model that simultaneously detects and segments disease spots on apples, peaches, oranges, and pears, he has created a robust, multi-fruit solution that dramatically improves detection efficiency and reliability. This work has direct implications for reducing post-harvest losses and enhancing food safety through automated quality sorting systems. Dr. Mou's contributions bridge the gap between deep learning architectures and practical agricultural applications, establishing a foundation for smart farming technologies that can operate in real-world, variable conditions. His research continues to influence the development of non-destructive, high-throughput fruit inspection systems.
Research Focus
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Top Papers
- 1