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Crop diseases pose a serious threat to international food security, and the development of automated intelligent systems for their identification remains a complex scientific and technical problem. The combination of the rise in global smartphone penetration and the latest advances in computer vision made possible by deep learning techniques has paved the way for disease diagnosis using all kinds of mobile devices. In order to develop high-precision image classifiers for diagnosing plant diseases, it is necessary to have a sufficiently large dataset of images of diseased and healthy plants.
MarSU has launched a digital crop production project aimed at finding anomalies in photos of apple trees using deep machine learning. The project team includes associate professors of the department of general agriculture, plant growing, agrochemistry and plant protection, candidates of agricultural sciences Nina Nikolaevna Apaeva and Asiya Mantsurovna Yamalieva, as well as professor of the department of agricultural engineering and production technology, processing of agricultural products, doctor of biological sciences Olga Gennadievna Maryina-Chermnykh.
Thanks to the scientific development of university scientists, it is possible to determine the disease with an accuracy of 96%. Neural networks analyze digitized images of the leaves and fruits of the apple tree and draw up a conclusion, which indicates the presence of a particular disease, which allows you to take measures to treat a specific disease.
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On December 13, 2021, for the first time, an intra-university student Olympiad in general hygiene and human ecology was held for foreign students (in English).
30.12.2021
"Leaders of MarSU" is an open personnel project for talented and perspective students from all over the university
11.05.2021