Age and gender recognition using multi-task CNN

Duc Quang Vu; Thi Thu Trang Phung; Chien Yao Wang; Jia Ching Wang

doi:10.1109/APSIPAASC47483.2019.9023045

Age and gender recognition using multi-task CNN

Duc Quang Vu, Thi Thu Trang Phung, Chien Yao Wang, Jia Ching Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

The investigation into age and gender identification has been receiving more attention from researchers since social and multimedia networks are becoming more popular nowadays. Recently published methods have yielded quite good results in terms of accuracy but have also proven to be ineffective in realtime applications because the models were too complicated. In this paper, we propose a lightweight model that can classify both age and gender. The number of parameters used in this model is 5 times less than existing models. Experiment results show that the accuracy of the proposed method is equivalent to state-of-the-art methods, while the speed of age and gender recognition decreases by 4 times on the Audience benchmark.

Original language	English
Title of host publication	2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1937-1941
Number of pages	5
ISBN (Electronic)	9781728132488
DOIs	https://doi.org/10.1109/APSIPAASC47483.2019.9023045
State	Published - Nov 2019
Event	2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 - Lanzhou, China Duration: 18 Nov 2019 → 21 Nov 2019

Publication series

Name	2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019

Conference

Conference	2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
Country/Territory	China
City	Lanzhou
Period	18/11/19 → 21/11/19

Access to Document

10.1109/APSIPAASC47483.2019.9023045

Deep Intelligence Based Spoken Language Processing( II )
Wang, J.-C. (PI)
1/01/19 → 31/12/19
Project: Research

Cite this

Vu, D. Q., Phung, T. T. T., Wang, C. Y., & Wang, J. C. (2019). Age and gender recognition using multi-task CNN. In 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 (pp. 1937-1941). Article 9023045 (2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APSIPAASC47483.2019.9023045

Vu, Duc Quang ; Phung, Thi Thu Trang ; Wang, Chien Yao et al. / Age and gender recognition using multi-task CNN. 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1937-1941 (2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019).

@inproceedings{bb19901bb5f94599ae07020cd892d351,

title = "Age and gender recognition using multi-task CNN",

abstract = "The investigation into age and gender identification has been receiving more attention from researchers since social and multimedia networks are becoming more popular nowadays. Recently published methods have yielded quite good results in terms of accuracy but have also proven to be ineffective in realtime applications because the models were too complicated. In this paper, we propose a lightweight model that can classify both age and gender. The number of parameters used in this model is 5 times less than existing models. Experiment results show that the accuracy of the proposed method is equivalent to state-of-the-art methods, while the speed of age and gender recognition decreases by 4 times on the Audience benchmark.",

author = "Vu, {Duc Quang} and Phung, {Thi Thu Trang} and Wang, {Chien Yao} and Wang, {Jia Ching}",

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series = "2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019",

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Vu, DQ, Phung, TTT, Wang, CY & Wang, JC 2019, Age and gender recognition using multi-task CNN. in 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019., 9023045, 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1937-1941, 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019, Lanzhou, China, 18/11/19. https://doi.org/10.1109/APSIPAASC47483.2019.9023045

Age and gender recognition using multi-task CNN. / Vu, Duc Quang; Phung, Thi Thu Trang; Wang, Chien Yao et al.
2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1937-1941 9023045 (2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The investigation into age and gender identification has been receiving more attention from researchers since social and multimedia networks are becoming more popular nowadays. Recently published methods have yielded quite good results in terms of accuracy but have also proven to be ineffective in realtime applications because the models were too complicated. In this paper, we propose a lightweight model that can classify both age and gender. The number of parameters used in this model is 5 times less than existing models. Experiment results show that the accuracy of the proposed method is equivalent to state-of-the-art methods, while the speed of age and gender recognition decreases by 4 times on the Audience benchmark.

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Vu DQ, Phung TTT, Wang CY, Wang JC. Age and gender recognition using multi-task CNN. In 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1937-1941. 9023045. (2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019). doi: 10.1109/APSIPAASC47483.2019.9023045

Age and gender recognition using multi-task CNN

Abstract

Publication series

Conference

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Projects

Deep Intelligence Based Spoken Language Processing( II )

Cite this