Papers
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About
M. S. Pryakhina is a researcher at the forefront of applying artificial intelligence to agricultural science, with a primary focus on phytosanitary monitoring and precision crop management. Her most notable contribution is the development of a convolutional neural network model for detecting and classifying diseases in fruit crops, specifically apple trees, using image analysis of leaves and fruits. In her landmark 2025 study, she employed transfer learning on the YOLOv10-X (You Only Look Once, version 10, Extra-large) model, pre-trained on a public dataset, to achieve high-accuracy disease identification. This work, which has already garnered 2 citations, represents a significant step toward automating early pest and disease detection, reducing reliance on manual scouting. Pryakhina’s research bridges deep learning and sustainable agriculture, offering scalable tools for real-time crop health monitoring. Her achievements highlight the growing role of neural networks in smart farming, positioning her as a key contributor to the digital transformation of phytosanitary practices.
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Top Papers
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