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- W3080209061 abstract "A novel algorithm for analysis and classification of breast abnormalities in digital mammography based on a deep convolutional neural network is proposed. Simplified neural network architectures such as MobileNetV2, InceptionResNetV2, Xception, and ResNetV2 are intensively studied for this task. In order to improve the accuracy of detection and classification of breast abnormalities on real data an efficient training algorithm based on augmentation technique is suggested. The performance of the proposed algorithm for analysis and classification of breast abnormalities on real data is discussed and compared to that of the state-of-the-art algorithms." @default.
- W3080209061 created "2020-09-01" @default.
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- W3080209061 date "2020-08-21" @default.
- W3080209061 modified "2023-09-27" @default.
- W3080209061 title "Classification of breast abnormalities in digital mammography with a deep convolutional neural network" @default.
- W3080209061 doi "https://doi.org/10.1117/12.2567252" @default.
- W3080209061 hasPublicationYear "2020" @default.
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