Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Haocheng Shen"'
Publikováno v:
IEEE Access, Vol 8, Pp 3901-3910 (2020)
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been increasingly used for lesion detection in breast cancer diagnosis for its capability to provide spatial-temporal information. However, the massive and complex 4D spatial-temporal
Externí odkaz:
https://doaj.org/article/cfe7c1c137e04ef0b8ef37e3445a8789
Publikováno v:
IEEE Access, Vol 8, Pp 133051-133062 (2020)
Anomaly detection aims to detect anomaly with only normal data available for training. It attracts considerable attentions in the medical domain, as normal data is relatively easy to obtain but it is rather difficult to have abnormal data especially
Externí odkaz:
https://doaj.org/article/f5fce0d5a3604662be83ec0e154f3827
Publikováno v:
Multimedia Tools and Applications. 81:5989-6008
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f985ed708f4252c2019db46cc899c36f
https://doi.org/10.1007/s11042-021-11814-y
https://doi.org/10.1007/s11042-021-11814-y
The ubiquity of camera-embedded devices and the advances in deep learning have stimulated various intelligent mobile video applications. These applications often demand on-device processing of video streams to deliver real-time, high-quality services
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8790bb488cfdab0ad743d319014987ee
http://arxiv.org/abs/2211.16135
http://arxiv.org/abs/2211.16135
Autor:
Chen Ren, Kuan Tian, Lijing Cai, Meng Yue, Dandan Han, Junzhou Huang, Jianhua Yao, Xiao Han, Pei Dong, Jun Zhang, Haocheng Shen, Yueping Liu, Xinran Wang, Lina Li, Jiuyan Shang, Hong Bu, Kezhou Yan, Shuyao Niu
Publikováno v:
Histopathology. 79:544-555
AIMS The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article wa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::997e93976dfa3a5c897dd2ecaa6813ed
https://doi.org/10.1111/his.14383
https://doi.org/10.1111/his.14383
Publikováno v:
ChemistrySelect. 7
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6fe5f81a676a8430ae1c445c1a5d9c01
https://doi.org/10.1002/slct.202201220
https://doi.org/10.1002/slct.202201220
Publikováno v:
IEEE Access, Vol 8, Pp 3901-3910 (2020)
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been increasingly used for lesion detection in breast cancer diagnosis for its capability to provide spatial-temporal information. However, the massive and complex 4D spatial-temporal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::858d13cc294f374c63836f0fdfc31963
https://ieeexplore.ieee.org/document/8944006/
https://ieeexplore.ieee.org/document/8944006/
Publikováno v:
IEEE Access, Vol 8, Pp 133051-133062 (2020)
Anomaly detection aims to detect anomaly with only normal data available for training. It attracts considerable attentions in the medical domain, as normal data is relatively easy to obtain but it is rather difficult to have abnormal data especially
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b4598c0665d48b0e76e9ee8d5ab486c
https://ieeexplore.ieee.org/document/9144563/
https://ieeexplore.ieee.org/document/9144563/
Publikováno v:
Computer Supported Cooperative Work and Social Computing ISBN: 9789811945489
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a1e117dd8c9a1e1f02bda7bec56ba0c
https://doi.org/10.1007/978-981-19-4549-6_18
https://doi.org/10.1007/978-981-19-4549-6_18
The blooming of fake news on social networks has devastating impacts on society, the economy, and public security. Although numerous studies are conducted for the automatic detection of fake news, the majority tend to utilize deep neural networks to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cfe6ac2b9905bbc37036cd5db73a159