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Fill-UNet: Extended Composite Semantic Segmentation
Q Liu, Y Zhao, W Ding, X Bu, N Hanajima - Applied Soft Computing, 2025 - Elsevier
The accuracy of image segmentation directly affects the precision of object recognition. To
address the limitations of the U-Net model in capturing global contextual information and …
address the limitations of the U-Net model in capturing global contextual information and …
HCMA-UNet: A Hybrid CNN-Mamba UNet with Inter-Slice Self-Attention for Efficient Breast Cancer Segmentation
H Li, P Qin, X Yuan, Z Chen - arxiv preprint arxiv:2501.00751, 2025 - arxiv.org
Breast cancer lesion segmentation in DCE-MRI remains challenging due to heterogeneous
tumor morphology and indistinct boundaries. To address these challenges, this study …
tumor morphology and indistinct boundaries. To address these challenges, this study …
Partial Label Learning via Cost-Guided Retraining
Z Zhang, Z Liu, H Lu - ECAI 2024, 2024 - ebooks.iospress.nl
In partial label learning, each training sample corresponds to a set of candidate labels. The
ground-truth label, hidden within this set, cannot be directly obtained during the training …
ground-truth label, hidden within this set, cannot be directly obtained during the training …
Deep-Learning based Identification of Suspicious Areas in Breast MRIs
BE Röthlin - 2024 - repositum.tuwien.at
Breast cancer is the most common cancer in women, accounting for 23.8% of female
cancers. Genetic testing or risk models using categorical variables are used to evaluate an …
cancers. Genetic testing or risk models using categorical variables are used to evaluate an …