Regular Section
Gender Attribute Mining with Hand-Dorsa Vein Image Based on Unsupervised Sparse Feature Learning
2018 Volume E101.D Issue 1 Pages 257-260
Details
2018 Volume E101.D Issue 1 Pages 257-260
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.
