您的評論: SwinUNeLCsT: Global–local spatial representation learning with hybrid CNN–transformer for efficient tuberculosis lung cavity weakly supervised semantic segmentation

SwinUNeLCsT: Global–local spatial representation learning with hybrid CNN–transformer for efficient tuberculosis lung cavity weakly supervised semantic segmentation

Radiological diagnosis of lung cavities (LCs) is the key to identifying tuberculosis (TB). Conventional deep learning methods rely on a large amount of accurate pixel-level data to segment LCs. This process is timeconsuming and laborious, especially for those subtle LCs. To address such challenges,...

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書目詳細資料
Main Authors:	Zhuoyi, Tan, Hizmawati, Madzin, Bahari, Norafida, Rahmita, Wirza OK Rahmat, Fatimah, Khalid, Puteri, Suhaiza Sulaiman
格式:	Article
語言:	English
出版:	Elsevier 2024
在線閱讀:	http://psasir.upm.edu.my/id/eprint/111381/1/SwinUNeLCsT.pdf
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SwinUNeLCsT: Global–local spatial representation learning with hybrid CNN–transformer for efficient tuberculosis lung cavity weakly supervised semantic segmentation

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