Performance estimation of the state-of-the-art convolution neural networks for thermal images-based gender classification system

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

Original language	American English
Journal	Journal of Electronic Imaging
DOIs	https://doi.org/10.1117/1.jei.29.6.063004
Publication status	Published - 18 Nov 2020

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title = "Performance estimation of the state-of-the-art convolution neural networks for thermal images-based gender classification system",

author = "Farooq, \{Muhammad Ali\} and Peter Corcoran",

year = "2020",

month = nov,

day = "18",

doi = "10.1117/1.jei.29.6.063004",

language = "American English",

journal = "Journal of Electronic Imaging",

issn = "1017-9909",

publisher = "SPIE",

}

TY - JOUR

T1 - Performance estimation of the state-of-the-art convolution neural networks for thermal images-based gender classification system

AU - Farooq, Muhammad Ali

AU - Corcoran, Peter

PY - 2020/11/18

Y1 - 2020/11/18

UR - http://dx.doi.org/10.1117/1.jei.29.6.063004

U2 - 10.1117/1.jei.29.6.063004

DO - 10.1117/1.jei.29.6.063004

M3 - Article

SN - 1017-9909

JO - Journal of Electronic Imaging

JF - Journal of Electronic Imaging

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