Impact of Type of Convolution Operation on Performance of Convolutional Neural Networks for Online Signature Verification-Reference-Cited by-同舟云学术

Impact of Type of Convolution Operation on Performance of Convolutional Neural Networks for Online Signature Verification

Published:2022 Issue: Volume: Page:83-97
ISSN:0302-9743
Container-title:Frontiers in Handwriting Recognition
language:
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Author:

Vorugunti Chandra Sekhar^ORCID,Subramanian Balasubramanian^ORCID,Gautam Avinash^ORCID,Pulabaigari Viswanath^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-21648-0_6

Reference42 articles.

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2. Al-Hmouz, R., Pedrycz, W., Daqrouq, K., Morfeq, A.: Quantifying dynamic time warping distance using probabilistic model in verification of dynamic signatures. Soft. Comput. 23(11), 407–418 (2019). https://doi.org/10.1007/s00500-017-2782-5

3. Lecture Notes in Computer Science;A Dutta,2020

4. Chandra Sekhar, V., Doctor, A., Viswanath, P.: A light weight and hybrid deep learning model based online signature verification. In: 2nd International Workshop on Machine Learning (ICDAR-WML), pp. 53–59 (2019)

5. Diaz, M., Fischer, A., Ferrer, M., Plamondon, R.: Dynamic signature verification system based on one real signature. IEEE Trans. Cybern. 48(1), 228–239 (2018)

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1. TSOSVNet: Teacher-student collaborative knowledge distillation for Online Signature Verification;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

2. OSVConTramer: A Hybrid CNN and Transformer based Online Signature Verification;2023 IEEE International Joint Conference on Biometrics (IJCB);2023-09-25