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Titlebook: Computational Forensics; 4th International Wo Hiroshi Sako,Katrin Y. Franke,Shuji Saitoh Conference proceedings 2011 Springer Berlin Heidel

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發(fā)表于 2025-3-21 16:03:40 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computational Forensics
副標題4th International Wo
編輯Hiroshi Sako,Katrin Y. Franke,Shuji Saitoh
視頻videohttp://file.papertrans.cn/233/232312/232312.mp4
概述up-to-date results.fast track conference proceedings.state-of-the-art report
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Forensics; 4th International Wo Hiroshi Sako,Katrin Y. Franke,Shuji Saitoh Conference proceedings 2011 Springer Berlin Heidel
描述This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Computational Forensics, IWCF 2010, held in Tokyo, Japan in November 2010. The 16 revised full papers presented together with two invited keynote papers were carefully selected during two rounds of reviewing and revision. The papers cover a wide range of current topics in computational forensics including authentication, biometrics, document analysis, multimedia, forensic tool evaluation, character recognition, and forensic verification.
出版日期Conference proceedings 2011
關鍵詞face recognition; finger print recognition; gestalt aspects; handwriting analysis; writer identification
版次1
doihttps://doi.org/10.1007/978-3-642-19376-7
isbn_softcover978-3-642-19375-0
isbn_ebook978-3-642-19376-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Berlin Heidelberg 2011
The information of publication is updating

書目名稱Computational Forensics影響因子(影響力)




書目名稱Computational Forensics影響因子(影響力)學科排名




書目名稱Computational Forensics網絡公開度




書目名稱Computational Forensics網絡公開度學科排名




書目名稱Computational Forensics被引頻次




書目名稱Computational Forensics被引頻次學科排名




書目名稱Computational Forensics年度引用




書目名稱Computational Forensics年度引用學科排名




書目名稱Computational Forensics讀者反饋




書目名稱Computational Forensics讀者反饋學科排名




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Second order vectors and forms,em based on contour features operating in identification mode (one-to-many) and working at the level of isolated characters. Individual characters of a writer are manually segmented and labeled by an expert as pertaining to one of 62 alphanumeric classes (10 numbers and 52 letters, including lowerca
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Riemannian manifolds and Brownian motions,ts. To extract the stroke order variation of an input character pattern, it is necessary to establish the accurate stroke correspondence between the input pattern and the reference pattern of the same category. In this paper we compare five stroke correspondence methods: the individual correspondenc
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Asymptotic Expansion and Weak Convergence, dental CT images is proposed. In the previous method, one of the main issue is the mis-extraction of the adjacent region caused by the similarity of feature between a tooth and its adjacent teeth or the surrounding alveolar bone. It is important to extract an accurate shape of the target tooth as a
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Gaussian Stochastic Calculus of Variations, work with highly degraded footwear marks and match them to the most similar footwear print available in the database. Retrieval process from a large database can be made significantly faster if the database footwear prints are clustered beforehand. In this paper we propose a footwear print retrieva
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https://doi.org/10.1007/3-540-30799-0ximum entropy method (MEM). The purpose of this study is to improve the efficiency of inkjet printer model identification based on spur mark comparison method (SCM) in the field of forensic document analysis. Experiments were performed using two spur gears in different color inkjet printer models. T
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Gaussian Stochastic Calculus of Variations,g diodes (LEDs). According to conventional methods indentations were observed by document examiners’ eyes using a microscope. However it is difficult to estimate depths of the indentations because human eyes only can observe shades and brightness made by indentations instead of measuring the depths
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