Hybrid machine learning techniques for gender identification from handwritten images using textural features
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-08931-1.pdf
Reference25 articles.
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2. Agarwal A, Saraswat M (2023) Analyzing various handwriting recognition phenomenon for predicting gender, age and handedness. In: Advancements in interdisciplinary research: 1st international conference, AIR 2022, Prayagraj, India, May 6–7, 2022, revised selected papers. Springer Nature, Cham, pp 224–234
3. Agduk S, Aydemir E (2022) Classification of handwritten text signatures by person and gender: a comparative study of transfer learning methods. Acta Informat Prag 2022(3):324–347
4. Alaei F, Alaei A (2022) Handwriting analysis: applications in person identification and forensic. Breakthroughs in digital biometrics and forensics. Springer, Cham, pp 147–165
5. AL-Qawasmeh NS (2022) Novel feature extraction methods to automatically detect gender and age from handwritten documents. Doctoral dissertation, Concordia University Montréal, QC, Canada
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