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Writer Identification Using Super Paramagnetic Clustering and Spatio Temporal Neural Network

机译:使用超顺磁聚类和时空神经网络的作家识别

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This paper discusses use of Super Paramagnetic Clustering (SPC) and Spatio Temporal Artificial Neuron in on-line writer identification, on Farsi handwriting. In online cases, speed and automation are advantages of one method on others, therefore we used unsupervised and relatively quick clustering method, which in comparison with conventional approaches, give us better result. Moreover, regardless of various parameters that available from acquisition systems, we only consider to displacement of pen tip at determined direction that lead to quick system due to its quick preprocessing and clustering. Also we use a threshold that remove displacement between disconnected point of a word that lead to a better classification result on on-line Farsi writers.
机译:本文讨论了使用超顺磁性聚类(SPC)和时空人工神经元进行波斯文字的在线作者识别。在在线情况下,速度和自动化是一种方法在其他方法上的优势,因此我们使用了无监督且相对较快的聚类方法,与传统方法相比,它可以提供更好的结果。此外,无论采集系统中可用的各种参数如何,我们都只考虑笔尖在确定方向上的位移,这归因于其快速的预处理和聚类,从而导致了快速的系统。同样,我们使用阈值来消除单词的断开点之间的位移,从而导致在线波斯语作者获得更好的分类结果。

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