EP
E.M. Pekalska
57 records found
1
Pattern Recognition
Introduction and Terminology
This ebook gives the starting student an introduction into the eld of pattern recognition. It may serve as reference to others by giving intuitive descriptions of the terminology. The book is the rst in a series of ebooks on topics and examples in the eld. Our goal is an informal
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Sometimesnoveloroutlierdatahastobedetected.Theoutliersmayindicatesomeinterestingrareevent,ortheyshouldbedisregardedbecausetheycannotbereliablyprocessedfurther.Intheidealcasethattheobjectsarerepresentedbyverygoodfeatures,thegenuinedataformsacompactclusterandagoodoutliermeasureisth
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StatisticallearningalgorithmsoftenrelyontheEuclideandistance.Inpractice,non-Euclideanornon-metricdissimilaritymeasuresmayarisewhencontours,spectraorshapesarecomparedbyeditdistancesorasaconsequenceofrobustobjectmatching[1,2].Itisanopenissuewhethersuchmeasuresareadvantageousforstat
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A common way of expressing string similarity in structural pattern recognition is the edit distance. It allows one to apply the kNN rule in order to classify a set of strings. However, compared to the wide range of elaborated classi¿ers known from statistical pattern recognition,
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Statisticalinferenceofsensor-basedmeasurementsisintensivelystudiedinpatternrecognition.Itisusuallybasedonfeaturerepresentationsoftheobjectstoberecognized.Suchrepresentations,however,neglecttheobjectstructure.Structuralpatternrecognition,onthecontrary,focussesonencodingtheobjectst
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