DFCNet specifications

Unique identifier:
OMICS_27005
Software type:
Application/Script
Restrictions to use:
None
Operating system:
Unix/Linux
Stability:
Stable
Name:
Deep Fully Convolutional neural Network
Interface:
Command line interface
Input data:
Some CT-Scan images.
Computer skills:
Advanced
Maintained:
Yes

versioning

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No versioning.

DFCNet support

Maintainer

  • Bin Sheng <>

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Credits

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Publications

Institution(s)

Dept. of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China; Dept. of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan; Faculty of Information Technology, Macau University of Science and Technology, Macau, Macau; Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China; School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong; School of Information Technologies, The University of Sydney, Sydney, VIC, Australia

Funding source(s)

Supported by the National Natural Science Foundation of China (No. 61572316, 61671290), National High-tech R&D Program of China (863 Program) (No. 2015AA015904), the Key Program for
International S&T Cooperation Project (No. 2016YFE0129500) of China, the Science and Technology Commission of Shanghai Municipality (No. 16DZ0501100, 17411952600), the General Program of Cross of Medicine and Engineering of SJTU (YG2015MS19), the interdisciplinary Program of Shanghai Jiao Tong University (No.14JCY10), a grant from the Research Grants Council of Hong Kong (No. 28200215), and a grant from The Hong Kong Polytechnic University (Project no. 1-ZE8J).

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