Sustainable Agriculture Volume 22 Issue 2 (2024) · pp. 106-109
PROCESSING OF BLOOD CELL IMAGES HYBRID METHODSOF ACUTE LYMPHOBLASTIC DIAGNOSIS CNN FEATURES
M.Ismailov, Ismailov, O.Ismailov, Temirova, X.Temirova
Abstract
CNN We will consider several image classification algorithms and models for the optimal deep learning model using Convolutional Neural Networks (CNN). Using deep learning of blood cell images, images of healthy blood samples are compared with blood samples of acute lymphoblastic leukemia (blood cancer in children and adults) and the data is compared to obtain an optimal model for early detection of the disease, and Python programming results are automated using the language. We have used CNN network 3 different machine learning hybrid algorithms and methods in the form of DenseNet121, ResNet50 and MobileNet below.
CNN; RF; XGBoost; ALL; PCA; hybrid method, DenseNet121, ResNet50 and MobileNet below.
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