Home | << 1 >> |
![]() |
Record | |||||
---|---|---|---|---|---|
Author | AN Ruchai; VI Kober; KA Dorofeev; VN Karnaukhov; Mikhail Mozerov | ||||
Title | Classification of breast abnormalities using a deep convolutional neural network and transfer learning | Type | Journal Article | ||
Year | 2021 | Publication | Journal of Communications Technology and Electronics | Abbreviated Journal | |
Volume | 66 | Issue | 6 | Pages | 778–783 |
Keywords | |||||
Abstract | 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. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference ![]() |
|||
Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ RKD2022 | Serial | 3680 | ||
Permanent link to this record |