Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Xianyong Fang"'
Parallel matters: Efficient polyp segmentation with parallel structured feature augmentation modules
Publikováno v:
IET Image Processing, Vol 17, Iss 8, Pp 2503-2515 (2023)
Abstract The large variations of polyp sizes and shapes and the close resemblances of polyps to their surroundings call for features with long‐range information in rich scales and strong discrimination. This article proposes two parallel structured
Externí odkaz:
https://doaj.org/article/1509ab8bb19f4a0ba658026e3a7be9c9
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 11 (2023)
Robust skin lesion segmentation of dermoscopic images is still very difficult. Recent methods often take the combinations of CNN and Transformer for feature abstraction and multi-scale features for further classification. Both types of combination in
Externí odkaz:
https://doaj.org/article/1de7bf91afef430dbbd8f6b1dff96516
Autor:
Qingqing Guo, Abdulla AlKendi, Xiaoping Jiang, Alberto Mittone, Linbo Wang, Emanuel Larsson, Alberto Bravin, Erik Renström, Xianyong Fang, Enming Zhang
Publikováno v:
Heliyon, Vol 9, Iss 2, Pp e13081- (2023)
Summary: The pancreatic islet is a highly structured micro-organ that produces insulin in response to rising blood glucose. Here we develop a label-free and automatic imaging approach to visualize the islets in situ in diabetic rodents by the synchro
Externí odkaz:
https://doaj.org/article/8698c0011581406685e4054baf9a4af1
Publikováno v:
IEEE Access, Vol 10, Pp 52971-52981 (2022)
Colorectal cancer is one of the leading causes of death worldwide. Polyps are early symptoms of colorectal cancer and prone to malignant transformation. Polyp segmentation of colonoscopy images can help diagnosis. However, existing studies on polyp s
Externí odkaz:
https://doaj.org/article/1553c28d3f984b8f9739ee40d4081ecf
Publikováno v:
Computer Modeling in Engineering & Sciences. 136:1835-1856
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce86c47766949794073e1168255b490d
https://doi.org/10.32604/cmes.2023.025662
https://doi.org/10.32604/cmes.2023.025662
Publikováno v:
International Journal of Machine Learning and Cybernetics. 14:1621-1633
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcc7509e2ca6426e7fee7b64319ee726
https://doi.org/10.1007/s13042-022-01716-2
https://doi.org/10.1007/s13042-022-01716-2
Publikováno v:
Multimedia Systems. 29:1717-1727
The transformational and spatial proximities are important cues for identifying inliers from an appearance based match set because correct matches generally stay close in input images and share similar local transformations. However, most existing ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fee3a3846092255562251e11c95e8c02
https://doi.org/10.1007/s00530-021-00792-8
https://doi.org/10.1007/s00530-021-00792-8
Publikováno v:
Cognitive Computation.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95e35d428a5e028600beaca6f619e696
https://doi.org/10.1007/s12559-022-10024-4
https://doi.org/10.1007/s12559-022-10024-4
Publikováno v:
IEEE Transactions on Cybernetics. 50:997-1008
Previous methods on text image motion deblurring seldom consider the sparse characteristics of the blur kernel. This paper proposes a new text image motion deblurring method by exploiting the sparse properties of both text image itself and kernel. It
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59e655c25c8172c314453e2b36ba0b7b
https://doi.org/10.1109/tcyb.2018.2876511
https://doi.org/10.1109/tcyb.2018.2876511
Publikováno v:
Pattern Recognition and Computer Vision ISBN: 9783031189128
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4edd2b7f727d8567301ce7a4eee6661
https://doi.org/10.1007/978-3-031-18913-5_1
https://doi.org/10.1007/978-3-031-18913-5_1
