Dimple Patil
Papers
1
Total Citations
55
H-Index
1
About
Dimple Patil is a leading researcher at the intersection of deep learning and sustainable agriculture, with a primary focus on real-time plant disease detection. Her most influential work, "Advancing real-time plant disease detection: A lightweight deep learning approach and novel dataset for pigeon pea crop" (2024, 55 citations), tackles a critical challenge in crop science: the unpredictable spread of diseases within plants. Patil’s major contribution lies in developing a lightweight deep learning model that enables efficient, real-time disease identification, overcoming the computational constraints that have hindered practical field deployment. By also introducing a novel dataset specifically for pigeon pea crops, she has provided a vital resource for the research community, bridging the gap between computer vision and agricultural sustainability. Her work is particularly notable for its emphasis on early disease treatment, directly supporting sustainable crop production and food security. Patil’s research demonstrates how advanced AI can be made accessible for real-world agricultural applications, making her a key figure in the growing field of precision agriculture.
Research Focus
Key Achievements
Top Papers
- 1