Face gender recognition based on 2D principal component analysis and support vector machine

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    9 Citations (Scopus)

    Abstract

    This paper presents a novel method for solving face gender recognition problem. This method employs 2D Principal Component Analysis, one of the prominent methods for extracting feature vectors, and Support Vector Machine, the most powerful discriminative method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.
    Original languageEnglish
    Title of host publication2010 Fourth International Conference on Network and System Security: NSS 2010
    Place of PublicationPiscataway, N.J., USA
    PublisherIEEE
    Pages579-582
    Number of pages4
    ISBN (Print)9781424484843
    DOIs
    Publication statusPublished - 2010
    EventFourth International Conference on Network and System Security (NSS 2010), - Melbourne, Australia
    Duration: 1 Sep 20103 Sep 2010

    Conference

    ConferenceFourth International Conference on Network and System Security (NSS 2010),
    CountryAustralia
    CityMelbourne
    Period1/09/103/09/10

    Fingerprint

    Face recognition
    Principal component analysis
    Support vector machines
    Experiments

    Cite this

    Tran, D., Huang, X., & Chetty, G. (2010). Face gender recognition based on 2D principal component analysis and support vector machine. In 2010 Fourth International Conference on Network and System Security: NSS 2010 (pp. 579-582). Piscataway, N.J., USA: IEEE. https://doi.org/10.1109/NSS.2010.19
    Tran, Dat ; Huang, Xu ; Chetty, Girija. / Face gender recognition based on 2D principal component analysis and support vector machine. 2010 Fourth International Conference on Network and System Security: NSS 2010. Piscataway, N.J., USA : IEEE, 2010. pp. 579-582
    @inproceedings{7daa17d5c65c44679ecc273a031a4e58,
    title = "Face gender recognition based on 2D principal component analysis and support vector machine",
    abstract = "This paper presents a novel method for solving face gender recognition problem. This method employs 2D Principal Component Analysis, one of the prominent methods for extracting feature vectors, and Support Vector Machine, the most powerful discriminative method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.",
    author = "Dat Tran and Xu Huang and Girija Chetty",
    year = "2010",
    doi = "10.1109/NSS.2010.19",
    language = "English",
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    Tran, D, Huang, X & Chetty, G 2010, Face gender recognition based on 2D principal component analysis and support vector machine. in 2010 Fourth International Conference on Network and System Security: NSS 2010. IEEE, Piscataway, N.J., USA, pp. 579-582, Fourth International Conference on Network and System Security (NSS 2010), Melbourne, Australia, 1/09/10. https://doi.org/10.1109/NSS.2010.19

    Face gender recognition based on 2D principal component analysis and support vector machine. / Tran, Dat; Huang, Xu; Chetty, Girija.

    2010 Fourth International Conference on Network and System Security: NSS 2010. Piscataway, N.J., USA : IEEE, 2010. p. 579-582.

    Research output: A Conference proceeding or a Chapter in BookConference contribution

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    Tran D, Huang X, Chetty G. Face gender recognition based on 2D principal component analysis and support vector machine. In 2010 Fourth International Conference on Network and System Security: NSS 2010. Piscataway, N.J., USA: IEEE. 2010. p. 579-582 https://doi.org/10.1109/NSS.2010.19