• July 3, 2022
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Glume pubescence prediction of spikelets using computer vision techniques

by Nikita | Novosibirsk State University Pubescence is the important feature, which has several useful functions. In that work we trained convolutional neural network for classification of wheat spikelets according to glume pubescence. Also we determined, what augmentations are the best for that task. These results can be used for training classification model of pubescence […]

13. Big genetic Data Analysis, deep learning, mathematical modeling and supercomputing
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  • June 22, 2022
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Bacteria species diversity on winter grain crops of the field ex-perimental station of RSAU-MTAA named after K.A. Timiryazev

by Olga Yu. Slovareva | Mufaro Muvingi | Anastasia B. Yaremko | Valentina S. Rubets | Vladimir N. Igonin | All-Russian Plant Quarantine Center, Bykovo, Russia | Peoples’ Friendship University of Russia, Moscow, Russia | All-Russian Plant Quarantine Center, Bykovo, Russia | Russian State Agrarian University – Moscow Agricultural Academy named after K.A. Timiryazev, Moscow, […]

5. Biotechnologies computational and experimental approaches
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