Gender classification using dorsal NIR hand veins imaging

• Published in: Neural computing & applications Vol. 37; no. 22; pp. 18275 - 18301
• Main Authors: Badawi, Ahmed, Saber, Alaa, Mohamed, Bassam, Shahin, Mohamed, Abdelrahman, Ahmed
• Format: Journal Article
• Language: English
• Published: London Springer London 01.08.2025; Springer Nature B.V
• Subjects: Accuracy; Age; Aging; Anthropology; Artificial Intelligence; Artificial neural networks; Biometric identification; Biometrics; Body mass index; Classification; Color imagery; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Customization; Data augmentation; Data Mining and Knowledge Discovery; Datasets; Fingerprints; Fingers; Gender; Geometry; Hand (anatomy); Image acquisition; Image Processing and Computer Vision; Indexing; Infrared imagery; Original Article; Probability and Statistics in Computer Science; Skin; Texture mapping; Varicose veins; Veins; Wrist; Biometrics; Convolutional neural networks; Gender classification; Near infrared; Dorsal hand veins; Multimodal score level fusion

Gender classification is soft biometric trait that can be used for identification, surveillance, databases-indexing, social/medical services, forensic anthropology, and e-marketing. Gender classification has been addressed with face, iris, fingerprints, hand veins of fingers/palm, and hand geometry....