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Gender Classification by Fuzzy Inference System : Classificazione di genere mediante un sistema di inferenza fuzzy, in: International Journal of Advanced Robotic Systems
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Información general
Autor Moallem, Payman; Mousavi, B. Somayeh
Publicado  InTech Open Access Publisher, 2013
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Abstract Gender classification from face images has many
applications and is thus an important research topic. This
paper presents an approach to gender classification based
on shape and texture information gathered to design a
fuzzy decision making system. Beside face shape features,
Zernik moments are applied as system inputs to improve
the system output which is considered as the probability
of being male face image. After parameters tuning of the
proposed fuzzy decision making system, 85.05%
classification rate on the FERET face database (including
1199 individuals from different poses and facial
expressions) shows acceptable results compare to other
methods.
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Superordinate work
 
no fulltext found International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Publicado: 2004
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Documents: International Journal of Advanced Robotic Systems
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DMG-Lib FaviconDMG-Lib https://www.dmg-lib.org/dmglib/handler?docum=32399009
Europeana FaviconEuropeana  http://www.europeana.eu/portal/record/2020801/dmglib_handler_docum_32399009.html
PDF FaviconPDF  Gender Classification by Fuzzy Inference System
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Administrative information
Time of publication 2013
License information Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License

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