IEICE TRANSACTIONS on Information
Gender Attribute Mining with Hand-Dorsa Vein Image Based on Unsupervised Sparse Feature Learning
Summary :
Gender classification with hand-dorsa vein information, a new soft biometric trait, is solved with the proposed unsupervised sparse feature learning model, state-of-the-art accuracy demonstrates the effectiveness of the proposed model. Besides, we also argue that the proposed data reconstruction model is also applicable to age estimation when comprehensive database differing in age is accessible.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.1 pp.257-260
- Publication Date
- 2018/01/01
- Publicized
- 2017/10/12
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017EDL8098
- Type of Manuscript
- LETTER
- Category
- Artificial Intelligence, Data Mining
Authors
Jun WANG
China University of Mining and Technology
Guoqing WANG
China University of Mining and Technology
Zaiyu PAN
China University of Mining and Technology
Keyword
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Jun WANG, Guoqing WANG, Zaiyu PAN, "Gender Attribute Mining with Hand-Dorsa Vein Image Based on Unsupervised Sparse Feature Learning" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 1, pp. 257-260, January 2018, doi: 10.1587/transinf.2017EDL8098.
Abstract: Gender classification with hand-dorsa vein information, a new soft biometric trait, is solved with the proposed unsupervised sparse feature learning model, state-of-the-art accuracy demonstrates the effectiveness of the proposed model. Besides, we also argue that the proposed data reconstruction model is also applicable to age estimation when comprehensive database differing in age is accessible.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017EDL8098/_p
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@ARTICLE{e101-d_1_257,
author={Jun WANG, Guoqing WANG, Zaiyu PAN, },
journal={IEICE TRANSACTIONS on Information},
title={Gender Attribute Mining with Hand-Dorsa Vein Image Based on Unsupervised Sparse Feature Learning},
year={2018},
volume={E101-D},
number={1},
pages={257-260},
abstract={Gender classification with hand-dorsa vein information, a new soft biometric trait, is solved with the proposed unsupervised sparse feature learning model, state-of-the-art accuracy demonstrates the effectiveness of the proposed model. Besides, we also argue that the proposed data reconstruction model is also applicable to age estimation when comprehensive database differing in age is accessible.},
keywords={},
doi={10.1587/transinf.2017EDL8098},
ISSN={1745-1361},
month={January},}
Copy
TY - JOUR
TI - Gender Attribute Mining with Hand-Dorsa Vein Image Based on Unsupervised Sparse Feature Learning
T2 - IEICE TRANSACTIONS on Information
SP - 257
EP - 260
AU - Jun WANG
AU - Guoqing WANG
AU - Zaiyu PAN
PY - 2018
DO - 10.1587/transinf.2017EDL8098
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2018
AB - Gender classification with hand-dorsa vein information, a new soft biometric trait, is solved with the proposed unsupervised sparse feature learning model, state-of-the-art accuracy demonstrates the effectiveness of the proposed model. Besides, we also argue that the proposed data reconstruction model is also applicable to age estimation when comprehensive database differing in age is accessible.
ER -
English
