Decision fusion for writer discrimination

dc.contributor.author	Ζώης, Ηλίας Ν.	el
dc.contributor.author	Αναστασόπουλος, Βασίλειος	el
dc.date.accessioned	2015-01-09T19:02:45Z
dc.date.issued	2015-01-09
dc.identifier.uri	http://hdl.handle.net/11400/3657
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	Discrimination system
dc.subject	Fusion, Latent heat of
dc.subject	Σύστημα διακρίσεων
dc.subject	Συγχώνευση
dc.title	Decision fusion for writer discrimination	en
heal.type	conferenceItem
heal.generalDescription	Proceedings	en
heal.classification	Electrical engineering
heal.classification	Electronics
heal.classification	Ηλεκτρολογική μηχανική
heal.classification	Ηλεκτρονική
heal.classificationURI	http://skos.um.es/unescothes/C01311
heal.classificationURI	http://zbw.eu/stw/descriptor/10455-2
heal.classificationURI	N/A-Ηλεκτρολογική μηχανική
heal.classificationURI	N/A-Ηλεκτρονική
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85052595
heal.identifier.secondary	10.1109/ICDSP.1997.628444
heal.dateAvailable	10000-01-01
heal.language	en
heal.access	forever
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Ηλεκτρονικών Μηχανικών Τ.Ε.	el
heal.publicationDate	1997
heal.bibliographicCitation	Zois, E. and Anastassopoulos, V. (1997). Decision fusion for writer discrimination. In the 13th International Conference on DigitalSignal Processing. vol. 2. Santorini, 2nd-4th July 1997. pp. 687 - 690.	en
heal.abstract	In this work the performance improvement of a one-word-based writer discrimination system is described. This is achieved when decision fusion is employed to combine the classification results (decisions) from N words. Only the binary classification problem (discriminate between two persons) is examined. In the proposed approach the randomized Neyman Pearson (N-P) test is applied. A special case of feature statistics is considered in order to fit the randomized N-P test and simultaneously achieve minimum classification error for each separate decision. Using only a few words the performance of the discrimination system is radically improved as far as the maximum classification error is concerned.	en
heal.publisher	[χ.ό.]	el
heal.fullTextAvailability	true
heal.conferenceName	International Conference on DigitalSignal Processing	en
heal.conferenceItemType	full paper