Zobrazeno 1 - 10
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pro vyhledávání: '"Zhu Wenhui"'
Retinal fundus photography enhancement is important for diagnosing and monitoring retinal diseases. However, early approaches to retinal image enhancement, such as those based on Generative Adversarial Networks (GANs), often struggle to preserve the
Externí odkaz:
http://arxiv.org/abs/2411.01403
With the rapid development of deep learning, CNN-based U-shaped networks have succeeded in medical image segmentation and are widely applied for various tasks. However, their limitations in capturing global features hinder their performance in comple
Externí odkaz:
http://arxiv.org/abs/2410.15036
In recent years, significant progress has been made in the medical image analysis domain using convolutional neural networks (CNNs). In particular, deep neural networks based on a U-shaped architecture (UNet) with skip connections have been adopted f
Externí odkaz:
http://arxiv.org/abs/2410.11578
Autor:
Dong, Xuanzhao, Vasa, Vamsi Krishna, Zhu, Wenhui, Qiu, Peijie, Chen, Xiwen, Su, Yi, Xiong, Yujian, Yang, Zhangsihao, Chen, Yanxi, Wang, Yalin
Retinal fundus photography is significant in diagnosing and monitoring retinal diseases. However, systemic imperfections and operator/patient-related factors can hinder the acquisition of high-quality retinal images. Previous efforts in retinal image
Externí odkaz:
http://arxiv.org/abs/2409.10966
Retinal fundus photography offers a non-invasive way to diagnose and monitor a variety of retinal diseases, but is prone to inherent quality glitches arising from systemic imperfections or operator/patient-related factors. However, high-quality retin
Externí odkaz:
http://arxiv.org/abs/2409.07862
Autor:
Yang, Zhangsihao, Shan, Mengyi, Farazi, Mohammad, Zhu, Wenhui, Chen, Yanxi, Dong, Xuanzhao, Wang, Yalin
Human video generation task has gained significant attention with the advancement of deep generative models. Generating realistic videos with human movements is challenging in nature, due to the intricacies of human body topology and sensitivity to v
Externí odkaz:
http://arxiv.org/abs/2409.01502
Autor:
Wang, Hao, Zhu, Wenhui, Qin, Jiayou, Li, Xin, Dumitrascu, Oana, Chen, Xiwen, Qiu, Peijie, Razi, Abolfazl
Detecting retinal image analysis, particularly the geometrical features of branching points, plays an essential role in diagnosing eye diseases. However, existing methods used for this purpose often are coarse-level and lack fine-grained analysis for
Externí odkaz:
http://arxiv.org/abs/2407.12271
Multiple instance learning (MIL) stands as a powerful approach in weakly supervised learning, regularly employed in histological whole slide image (WSI) classification for detecting tumorous lesions. However, existing mainstream MIL methods focus on
Externí odkaz:
http://arxiv.org/abs/2407.03575
Autor:
Zhu, Wenhui, Chen, Xiwen, Qiu, Peijie, Farazi, Mohammad, Sotiras, Aristeidis, Razi, Abolfazl, Wang, Yalin
Since its introduction, UNet has been leading a variety of medical image segmentation tasks. Although numerous follow-up studies have also been dedicated to improving the performance of standard UNet, few have conducted in-depth analyses of the under
Externí odkaz:
http://arxiv.org/abs/2406.14896
Autor:
Guo Linhao, Hu Zelin, Wan Rongqiao, Long Linyun, Li Tao, Yan Jianchang, Lin Yun, Zhang Lei, Zhu Wenhui, Wang Liancheng
Publikováno v:
Nanophotonics, Vol 8, Iss 1, Pp 171-180 (2018)
Ultraviolet (UV) photonics-based device and equipment have various applications in sterilization, military covert communication, medical treatment, nanofabrication, gem identification and so on. The traditional constituent UV components are bulky, in
Externí odkaz:
https://doaj.org/article/3ea03d79d9fd45c39f732b279731c844
