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Highly Robust Statistical Methods in Medical Image Analysis
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SYSNO ASEP 0369205 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Highly Robust Statistical Methods in Medical Image Analysis Author(s) Kalina, Jan (UIVT-O) RID, SAI, ORCID Source Title Biocybernetics and Biomedical Engineering. - : Elsevier - ISSN 0208-5216
Roč. 32, č. 2 (2012), s. 3-16Number of pages 14 s. Language eng - English Country PL - Poland Keywords robust statistics ; classification ; faces ; robust image analysis ; forensic science Subject RIV BB - Applied Statistics, Operational Research R&D Projects 1M06014 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000305102200001 EID SCOPUS 84861979582 DOI 10.1016/S0208-5216(12)70033-5 Annotation Standard multivariate statistical methods in medical applications are too sensitive to the assumption of multivariate normality and the presence of outliers in the data. This paper is devoted to robust statistical methods. In the context of medical image analysis they allow to solve the tasks of face detection and face recognition in a database of images. The results of the robust approaches in image analysis turn out to outperform those obtained with standard methods. Robust methods also have desirable properties appealing for practical applications, including dimension reduction and clear interpretability. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2013 Electronic address http://www.ibib.waw.pl/bbe/bbefulltext/BBE_32_2_003_FT.pdf
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