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Titlebook: Applied Pattern Recognition; Horst Bunke,Abraham Kandel,Mark Last Book 2008 Springer-Verlag Berlin Heidelberg 2008 Markov.Statistica.Wavel

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1860-949X accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new task
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https://doi.org/10.1007/978-3-642-48598-5 the handwriting features. Our experiments show this novel method, compared with two-dimensional Gabor model, one classic method on off- line, text-independent writer identification, not only achieves much better identifi- cation results but also greatly reduces the elapsed time on calculation.
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A Wavelet-based Statistical Method for Chinese Writer Identification the handwriting features. Our experiments show this novel method, compared with two-dimensional Gabor model, one classic method on off- line, text-independent writer identification, not only achieves much better identifi- cation results but also greatly reduces the elapsed time on calculation.
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