Anita Shrotriya
Papers
1
Total Citations
2
H-Index
1
About
Anita Shrotriya is a researcher at the forefront of applying artificial intelligence to agricultural challenges, with a particular focus on plant disease detection. Her work centers on developing and optimizing deep learning models for identifying diseased leaves through image analysis, a critical area for improving crop yield and food security. In her most-cited paper, "Performance Evaluation of Image-Based Diseased Leaf Identification Model Using CNN and GA" (2022), Shrotriya demonstrates a novel integration of Convolutional Neural Networks (CNNs) with Genetic Algorithms (GA) to enhance the accuracy and efficiency of leaf disease classification. This hybrid approach not only advances computational methods in precision agriculture but also offers a scalable solution for real-world farming applications. With 2 citations and growing recognition, her contributions are paving the way for smarter, data-driven agricultural practices. Shrotriya’s work exemplifies the transformative potential of AI in addressing pressing environmental and agricultural issues, making her a promising voice in the intersection of computer vision and sustainable farming.
Research Focus
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Top Papers
- 1