|
|
|
Ruoyang Li, Shuping Xiong, Yinchao Che, Lei Shi, Xinming Ma and Lei Xi
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentation ...
ver más
|
|
|
|
|
|
Xin Chen, Peng Shi and Yi Hu
Semantic segmentation methods have been successfully applied in seabed sediment detection. However, fast models like YOLO only produce rough segmentation boundaries (rectangles), while precise models like U-Net require too much time. In order to achieve ...
ver más
|
|
|
|
|
|
Nahida Nazir, Abid Sarwar, Baljit Singh Saini and Rafeeya Shams
Cervical cancer poses a significant global health burden, affecting women worldwide. Timely and accurate detection is crucial for effective treatment and improved patient outcomes. The Pap smear test has long been a standard cytology screening method, en...
ver más
|
|
|
|
|
|
Mohammed Chekroun, Youssef Mourchid, Igor Bessières and Alain Lalande
The advent of the 0.35 T MR-Linac (MRIdian, ViewRay) system in radiation therapy allows precise tumor targeting for moving lesions. However, the lack of an automatic volume segmentation function in the MR-Linac?s treatment planning system poses a challen...
ver más
|
|
|
|
|
|
Yaowei Feng, Zhendong Li, Dong Yang, Hongkai Hu, Hui Guo and Hao Liu
The segmentation of optic disc (OD) and optic cup (OC) are used in the automatic diagnosis of glaucoma. However, the spatially ambiguous boundary and semantically uncertain region-of-interest area in pictures may lead to the degradation of the performanc...
ver más
|
|
|