Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Shangshang Ding"'
Autor:
Xiaodong Yang, Hua Liu, Tianli Zheng, Shuang Jiang, Weiwei Fu, Shangshang Ding, Daoliang Xv, Hetong Zhang, Tianyou Zheng
Publikováno v:
BMJ Open, Vol 14, Iss 2 (2024)
Introduction The worldwide prevalence of myopia is high and continues to increase. In this study, a school screening programme for myopia will be implemented using the whole-process information method. The purpose of this study is to investigate the
Externí odkaz:
https://doaj.org/article/98b19eaa1d8b49b38274213b4667db30
Publikováno v:
BioMedical Engineering OnLine, Vol 21, Iss 1, Pp 1-14 (2022)
Abstract Background Refractive error detection is a significant factor in preventing the development of myopia. To improve the efficiency and accuracy of refractive error detection, a refractive error detection network (REDNet) is proposed that combi
Externí odkaz:
https://doaj.org/article/d39840ea9165471fb5ca1907682a784a
Publikováno v:
IEEE Photonics Journal, Vol 13, Iss 3, Pp 1-18 (2021)
Activity level measurement and fusion rules are the two key factors of image fusion. In the fusion method based on neural networks, the activity level measurements are realized by dividing the image into small blocks and predicting the sharpness of e
Externí odkaz:
https://doaj.org/article/cb9264a0622143bbb1aa056cb8c9ae1b
Publikováno v:
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation. 46(4)
In order to better assist doctors in the diagnosis of dry eye and improve the ability of ophthalmologists to recognize the condition of meibomian gland, a meibomian gland image segmentation and enhancement method based on Mobile-U-Net network was pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::8020e859fe6b9654cad808c10e5a8129
https://pubmed.ncbi.nlm.nih.gov/35929150
https://pubmed.ncbi.nlm.nih.gov/35929150
Publikováno v:
IEEE Photonics Journal, Vol 13, Iss 3, Pp 1-18 (2021)
Activity level measurement and fusion rules are the two key factors of image fusion. In the fusion method based on neural networks, the activity level measurements are realized by dividing the image into small blocks and predicting the sharpness of e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1134f603f6d5c48a9220185c0a6f1f8
https://ieeexplore.ieee.org/document/9403870/
https://ieeexplore.ieee.org/document/9403870/