| dc.contributor.author | Zhao, Di | ru |
| dc.contributor.author | Tang, Yi | ru |
| dc.contributor.author | Gourinovitch, A. | ru |
| dc.contributor.author | Liankova, A. | ru |
| dc.coverage.spatial | Минск | ru |
| dc.date.accessioned | 2023-11-11T08:51:20Z | |
| dc.date.available | 2023-11-11T08:51:20Z | |
| dc.date.issued | 2023 | |
| dc.identifier.citation | Zhao, Di. Exploring the role of loss functions in biomedical image segmentation / Di Zhao [и др.] // Беларусь-Китай: контуры инновационно-технологического сотрудничества : сборник материалов научно-практической конференции (Минск, 19-20 октября 2023 г.) // Республиканское инновационное унитарное предприятие «Научно-технологический парк БНТУ «Политехник» ; сост. М. А. Войтешонок. – Минск : БНТУ, 2023. – С. 66-67. | ru |
| dc.identifier.uri | https://rep.bntu.by/handle/data/137126 | |
| dc.description.abstract | The loss function is an important part of the segmentation method based on deep learning, and the improvement of the loss function can improve the segmentation effect of the network from the root, however, there are few literatures to do specific analysis and summary of various types of loss functions, this paper summaries some commonly used loss functions from the common problems in the current medical image segmentation task. | ru |
| dc.language.iso | en | ru |
| dc.publisher | БНТУ | ru |
| dc.title | Exploring the role of loss functions in biomedical image segmentation | ru |
| dc.type | Working Paper | ru |
