10 April 2018 Offline signature verification using convolution Siamese network
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Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106151I (2018) https://doi.org/10.1117/12.2303380
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China
Abstract
This paper presents an offline signature verification approach using convolutional Siamese neural network. Unlike the existing methods which consider feature extraction and metric learning as two independent stages, we adopt a deepleaning based framework which combines the two stages together and can be trained end-to-end. The experimental results on two offline public databases (GPDSsynthetic and CEDAR) demonstrate the superiority of our method on the offline signature verification problem.
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Zi-Jian Xing, Zi-Jian Xing, Fei Yin, Fei Yin, Yi-Chao Wu, Yi-Chao Wu, Cheng-Lin Liu, Cheng-Lin Liu, } "Offline signature verification using convolution Siamese network", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106151I (10 April 2018); doi: 10.1117/12.2303380; https://doi.org/10.1117/12.2303380
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