Geodesic
Neural network model and classifier training algorithm for processing human serum gel electrophoresis data
Problemy fiziki, matematiki i tehniki, no. 4 (2024), pp. 70-77

Voir la notice de l'article provenant de la source Math-Net.Ru

The analysis of biomedical images of proteinograms obtained as a result of gel electrophoresis is a research area of current interest. As a result of the study of various methods and means of analyzing electrophoregrams, the authors proposed a resource-efficient and fast model of convolutional neural network, which allows the classification of human blood serum proteinograms with high accuracy at low requirements to computing resources of the computer.
Keywords: neural networks, computer vision, image recognition, proteinograms, electrophoresis. 
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     title = {Neural network model and classifier training algorithm for processing human serum gel electrophoresis data},
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K. S. Kurochka; K. A. Panarin; K. S. Makeeva. Neural network model and classifier training algorithm for processing human serum gel electrophoresis data. Problemy fiziki, matematiki i tehniki, no. 4 (2024), pp. 70-77. http://geodesic.mathdoc.fr/item/PFMT_2024_4_a11/