COMPOSV++: Light Weight Online Signature Verification Framework Through Compound Feature Extraction and Few-Shot Learning-Reference-Cited by-同舟云学术

COMPOSV++: Light Weight Online Signature Verification Framework Through Compound Feature Extraction and Few-Shot Learning

Published:2022 Issue: Volume: Page:98-111
ISSN:0302-9743
Container-title:Frontiers in Handwriting Recognition
language:
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Author:

Vorugunti Chandra Sekhar^ORCID,Subramanian Balasubramanian^ORCID,Mukherjee Prerana^ORCID,Gautam Avinash^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-21648-0_7

Reference38 articles.

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2. Sekhar, C., Sai, G., Viswanath, P.: Online signature verification by few-shot separable convolution based deep learning. In: 15th International Conference on Document Analysis and Recognition (ICDAR 2019) Sydney, Australia, pp. 1125–1129 (2019)

3. Vorugunti, S., Anoushka, D., Prerana, M., Viswanath, P.: A light weight and hybrid deep learning model based online signature verification. In: ICDAR WML 2019 2nd International Workshop on Machine Learning, 2019, pp. 53–59 (2019)

4. Koushik, M., Shantharamu, M., Devanur, G., Somashekara, M.T.: Online signature verification based on writer dependent features and classifiers. Pattern Recogn. Lett. 80, 129–136 (2016)

5. Chandra, V., Devanur, G., Pulabaigari, V.: An efficient online signature verification based on feature fusion and interval valued representation of writer dependent features. In: IEEE 5th International Conference on Identity, Security and Behavior Analysis (ISBA) (2019)