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Author Identification from Handwritten Characters using Siamese CNN

机译:使用暹罗CNN的手写字符的作者识别

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The NIST Special Database 19 has been studied to solve character recognition tasks. We present a different study on this dataset, where we do author identification using features learned from handwritten characters. Recent studies in computer vision demonstrate that Siamese Convolutional Networks enjoyed successes in image information retrieval tasks. This technique has previously been applied in the identification of people using face image data producing start-of-the-art performance. We apply Siamese convolutional neural networks in author verification based on the handwritten characters. Employing a pairwise-loss approach, we developed a three-layer Convolutional Neural Network, with three fully connected layers, we achieved verification accuracy of 80% on average with unseen test data.
机译:NIST特殊数据库19已经研究过解决字符识别任务。我们对此数据集进行了不同的研究,在那里我们使用从手写字符中学到的功能进行作者标识。最近的计算机愿景的研究表明,暹罗卷积网络在图像信息检索任务中享有成功。此技术先前已应用于使用产生最新性能的面部图像数据的人们的识别。我们在基于手写字符的作者验证中应用暹罗卷积神经网络。采用成对损耗方法,我们开发了一个三层卷积神经网络,具有三个完全连接的层,我们平均实现了80%的验证精度,看不见的试验数据。

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