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Titlebook: Handwriting Recognition; Soft Computing and P Zhi-Qiang Liu,Jinhai Cai,Richard Buse Book 2003 Springer-Verlag Berlin Heidelberg 2003 Markov

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书目名称Handwriting Recognition
副标题Soft Computing and P
编辑Zhi-Qiang Liu,Jinhai Cai,Richard Buse
视频video
概述A fresh look at the problem of unconstrained handwriting recognition from the soft computing viewpoint
丛书名称Studies in Fuzziness and Soft Computing
图书封面Titlebook: Handwriting Recognition; Soft Computing and P Zhi-Qiang Liu,Jinhai Cai,Richard Buse Book 2003 Springer-Verlag Berlin Heidelberg 2003 Markov
描述Over the last few decades, research on handwriting recognition has made impressive progress. The research and development on handwritten word recognition are to a large degree motivated by many application areas, such as automated postal address and code reading, data acquisition in banks, text-voice conversion, security, etc. As the prices of scanners, com­ puters and handwriting-input devices are falling steadily, we have seen an increased demand for handwriting recognition systems and software pack­ ages. Some commercial handwriting recognition systems are now available in the market. Current commercial systems have an impressive performance in recognizing machine-printed characters and neatly written texts. For in­ stance, High-Tech Solutions in Israel has developed several products for container ID recognition, car license plate recognition and package label recognition. Xerox in the U. S. has developed TextBridge for converting hardcopy documents into electronic document files. In spite of the impressive progress, there is still a significant perfor­ mance gap between the human and the machine in recognizing off-line unconstrained handwritten characters and words. The difficu
出版日期Book 2003
关键词Markov; algorithm; algorithms; fuzzy; fuzzy set; hidden markov model; logic; model; learning and instruction
版次1
doihttps://doi.org/10.1007/978-3-540-44850-1
isbn_softcover978-3-642-07280-2
isbn_ebook978-3-540-44850-1Series ISSN 1434-9922 Series E-ISSN 1860-0808
issn_series 1434-9922
copyrightSpringer-Verlag Berlin Heidelberg 2003
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Zhi-Qiang Liu,Jinhai Cai,Richard Buseagnetic field (~1.10 kA/m and 200 kHz), and the heat generated by them was assessed by an infrared camera. The resulting thermal images were processed in MATLAB after the thermographic calibration of the infrared camera. The results show the potential to use this thermal technique for the improvement and advance of MFH as a clinical therapy.
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Zhi-Qiang Liu,Jinhai Cai,Richard Buseing;virtual reality; observing humans; spectral imaging and processing; intelligenttransportation systems; visual perception and robotic systems. Part II (LNCS9475): applications; 3D computer vision; computer graphics; segmentation;biometrics; pattern recognition; recognition; and virtual reality..
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Markov Models with Spectral Features for Handwritten Numeral Recognition,introduces Fourier descriptors for spectral features. Section 4.3 presents the Markov model-based method for recognizing handwritten numerals. This chapter also presents efficient re-estimation and evaluation algorithms. The results of handwritten numeral recognition using the proposed method are given in Section 4.4.
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Markov Random Field Models for Recognizing Handwritten Words,ng measurements. The relaxation labeling algorithm is used to maximize the global compatibilities of the MRF models. We investigate the influence of neighborhood size and iteration number of relaxation labeling on recognition rates.
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1434-9922 handwriting recognition has made impressive progress. The research and development on handwritten word recognition are to a large degree motivated by many application areas, such as automated postal address and code reading, data acquisition in banks, text-voice conversion, security, etc. As the pr
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que is developed to address these new challenges by means of an advancing front guided by a sphere packing methodology. The method is fairly simple and can efficiently triangulate point clouds into high quality meshes. The substantiated experimental results demonstrate the robustness and the generality of the proposed method.
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