Recurrent Binary Patterns and CNNs for Offline Signature Verification

Author:

Yılmaz Mustafa Berkay,Öztürk Kağan

Publisher

Springer International Publishing

Reference37 articles.

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2. Galbally, J., Gomez-Barrero, M., Ross, A.: Accuracy evaluation of handwritten signature verification: rethinking the random-skilled forgeries dichotomy. In: 2017 IEEE International Joint Conference on Biometrics (IJCB), pp. 302–310 (2017)

3. Graves, A., Schmidhuber, J.: Offline handwriting recognition with multidimensional recurrent neural networks. In: Koller, D., Schuurmans, D., Bengio, Y., Bottou, L. (eds.) Advances in Neural Information Processing Systems 21, pp. 545–552. Curran Associates Inc., Red Hook (2009)

4. Byeon, W., Breuel, T.M., Raue, F., Liwicki, M.: Scene labeling with LSTM recurrent neural networks. In: CVPR, pp. 3547–3555. IEEE Computer Society (2015)

5. Visin, F., Kastner, K., Cho, K., Matteucci, M., Courville, A., Bengio, Y.: ReNet: a recurrent neural network based alternative to convolutional networks. arXiv preprint arXiv:1505.00393 (2015)

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