Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Muhammad Bilal Zia"'
Autor:
Muhammad Bilal Zia
Publikováno v:
IEEE Access, Vol 12, Pp 170161-170175 (2024)
Accurate detection of parasitic eggs can help veterinarians detect issues in the early stages of infection, ensuring timely and effective treatment. However, existing methods are prone to losing the critical location information of the target parasit
Externí odkaz:
https://doaj.org/article/c332c19bba9441eda4b2640a11a901b2
Publikováno v:
International Journal of Machine Learning and Cybernetics. 13:1283-1299
Kirsten Ras (KRAS) mutation identification has great clinical significance to formulate the rectal cancer treatment scheme. Recently, the development of deep learning does much help to improve the computer-aided diagnosis technology. However, deep le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ef393257e1f5b05758482d4fe050ede
https://doi.org/10.1007/s13042-021-01447-w
https://doi.org/10.1007/s13042-021-01447-w
Publikováno v:
International Journal of Hybrid Information Technology. 13:45-56
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eec3cc267777f2d2b8b708e86d5a5d48
https://doi.org/10.21742/ijhit.2020.13.2.04
https://doi.org/10.21742/ijhit.2020.13.2.04
Publikováno v:
IET Image Processing. 14:1690-1700
Positron emission tomography (PET) image reconstruction from low-count projection data and physical effects is challenging because the inverse problem is ill-posed and the resultant image is usually noisy. Recently, generative adversarial networks (G
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62ff0a6261eeb4b1887cd71b7628de23
https://doi.org/10.1049/iet-ipr.2019.1107
https://doi.org/10.1049/iet-ipr.2019.1107
Publikováno v:
Oncol Lett
Early identification and classification of pulmonary nodules are essential for improving the survival rates of individuals with lung cancer and are considered to be key requirements for computer-assisted diagnosis. To address this topic, the present
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c512ff97c045b27f1fa73c0378404eaa
https://doi.org/10.3892/ol.2020.11576
https://doi.org/10.3892/ol.2020.11576
Publikováno v:
International Journal of Computer Applications. 177:23-28
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af36fc3d0631db2944c3b18ae7f712df
https://doi.org/10.5120/ijca2019919741
https://doi.org/10.5120/ijca2019919741
Autor:
Yan Qiang, Juanjuan Zhao, Guohua Shi, Wenkai Yang, Muhammad Bilal Zia, Xiaotang Yang, Qianqian Du, Yunyun Dong
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030322502
MICCAI (4)
MICCAI (4)
Semi-supervised learning can reduce the burden of manual label data and improve classification performance by learning with unlabelled data. However, due to the absence of label constraints, unlabelled data is usually ambiguous, which typically resul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83bb6eca76d7f748a815cc36f3d386b5
https://doi.org/10.1007/978-3-030-32251-9_61
https://doi.org/10.1007/978-3-030-32251-9_61
Autor:
Muhammad Bilal Zia, Juanjuan Zhao, Kun Wu, Wenkai Yang, Yunyun Dong, Xiaotang Yang, Qianqian Du, Yan Qiang
Publikováno v:
Engineering Applications of Artificial Intelligence. 98:104064
The automatic and accurate diagnosis of thyroid nodules in ultrasound images is of great significance to reduce the workload and radiologists’ misdiagnosis rate. Although deep learning has shown strong image classification performance, the inherent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d5a7b5e04c140299c0d5e8882e50e22a
https://doi.org/10.1016/j.engappai.2020.104064
https://doi.org/10.1016/j.engappai.2020.104064