TY - JOUR AU - AN Ruchai AU - VI Kober AU - KA Dorofeev AU - VN Karnaukhov AU - Mikhail Mozerov PY - 2021// TI - Classification of breast abnormalities using a deep convolutional neural network and transfer learning JO - Journal of Communications Technology and Electronics SP - 778–783 VL - 66 IS - 6 N2 - A new algorithm for classification of breast pathologies in digital mammography using a convolutional neural network and transfer learning is proposed. The following pretrained neural networks were chosen: MobileNetV2, InceptionResNetV2, Xception, and ResNetV2. All mammographic images were pre-processed to improve classification reliability. Transfer training was carried out using additional data augmentation and fine-tuning. The performance of the proposed algorithm for classification of breast pathologies in terms of accuracy on real data is discussed and compared with that of state-of-the-art algorithms on the available MIAS database. UR - https://link.springer.com/article/10.1134/S1064226921060206 UR - http://dx.doi.org/10.1134/S1064226921060206 N1 - LAMP; ID - AN Ruchai2021 ER -