Computer Methods and Programs in Biomedicine, Год журнала: 2024, Номер 247, С. 108080 - 108080
Опубликована: Фев. 15, 2024
Язык: Английский
Computer Methods and Programs in Biomedicine, Год журнала: 2024, Номер 247, С. 108080 - 108080
Опубликована: Фев. 15, 2024
Язык: Английский
Information Fusion, Год журнала: 2024, Номер 105, С. 102227 - 102227
Опубликована: Янв. 6, 2024
Язык: Английский
Процитировано
9CAAI Transactions on Intelligence Technology, Год журнала: 2024, Номер 9(4), С. 837 - 849
Опубликована: Апрель 8, 2024
Abstract Convolutional neural networks depend on deep network architectures to extract accurate information for image super‐resolution. However, obtained of these convolutional cannot completely express predicted high‐quality images complex scenes. A dynamic super‐resolution (DSRNet) is presented, which contains a residual enhancement block, wide feature refinement block and construction block. The composed enhanced architecture facilitate hierarchical features To enhance robustness model scenes, achieves learn more robust applicability an varying prevent interference components in utilises stacked accurately features. Also, learning operation embedded the long‐term dependency problem. Finally, responsible reconstructing images. Designed heterogeneous can not only richer structural information, but also be lightweight, suitable mobile digital devices. Experimental results show that our method competitive terms performance, recovering time complexity. code DSRNet at https://github.com/hellloxiaotian/DSRNet .
Язык: Английский
Процитировано
9Microchemical Journal, Год журнала: 2024, Номер 199, С. 110034 - 110034
Опубликована: Янв. 26, 2024
Язык: Английский
Процитировано
8Biomedical Signal Processing and Control, Год журнала: 2024, Номер 95, С. 106316 - 106316
Опубликована: Апрель 26, 2024
Язык: Английский
Процитировано
8Computer Methods and Programs in Biomedicine, Год журнала: 2024, Номер 247, С. 108080 - 108080
Опубликована: Фев. 15, 2024
Язык: Английский
Процитировано
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