INNOVATIONS IN NEURAL NETWORKS AND THEIR IMAGE RECOGNITION

sayyora iskandarova; Dilshod Eshmuradov; Fotima Tulaganova

Авторы

sayyora iskandarova Tashkent University of Information Technologies named after Muhammad al-Khwarizmi
Dilshod Eshmuradov Tashkent University of Information Technologies named after Muhammad al-Khwarizmi
Fotima Tulaganova Tashkent University of Information Technologies named after Muhammad al-Khwarizmi

Ключевые слова:

Leukocytes, blood disorders, chromatic properties, geometric patterns, texture features, neural network, automated algorithm, classification, microscopic sample

Аннотация

Leukocytes (white blood cells) play a significant role in the processes of blood cell identification and classification. This study considers the application of neural network algorithms for the automatic analysis of blood cell microscopic samples. This method especially focuses on identifying chromatic, geometric, and textural features of leukocytes. An advanced solution is provided for early diagnosing blood Related diseases through image processing and artificial intelligence. Automated systems allow not only to shorten the analysis period but also to reduce the number of errors made by experts. The purpose of this work is to create an efficient neural network algorithm for classification of blood cells samples in order to help in early detection of diseases related to leukocytes. In this study, the efficiency of training models with different architectures of neural networks, namely Recurrent Neural Networks (RNN), ResNet (Residual Network) and Convolutional Neural Networks (CNN), was compared by using different parameters.

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