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SynSig2Vec: Learning Representations from Synthetic Dynamic Signatures for Real-world Verification
To tackle this issue, this paper proposes to learn dynamic signature representations through ranking synthesized signatures.
Recognition Confidence Analysis of Handwritten Chinese Character with CNN
In this paper, we present an effective method to analyze the recognition confidence of handwritten Chinese character, based on the softmax regression score of a high performance convolutional neural networks (CNN).
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