Gender Detection Using Random Forest
Author:
Affiliation:
1. Department of Computer System Design, Benghazi University, Benghazi, Libya
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3410352.3410799
Reference21 articles.
1. An approach to improve Palmprint Recognition Accuracy by Using Different Region of Interest Methods with Local Binary Pattern Techniques
2. Al Mashagba E. F. 2016. Real-time gender classification by face. Int J Adv Comput Sci Appl 7(3). DOI= http://dx.doi.org/10.3906/elk-1203-51. Al Mashagba E. F. 2016. Real-time gender classification by face. Int J Adv Comput Sci Appl 7(3). DOI= http://dx.doi.org/10.3906/elk-1203-51.
3. Face analysis through semantic face segmentation
4. Descriptors and regions of interest fusion for in- and cross-database gender classification in the wild
5. Evaluation of gender classification methods on thermal and near-infrared face images
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