Pictorial Information-Retrieval Using the Random Neural Network

dc.contributor.authorStafylopatis, A.en
dc.contributor.authorLikas, A.en
dc.date.accessioned2015-11-24T17:00:22Z
dc.date.available2015-11-24T17:00:22Z
dc.identifier.issn0098-5589-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/10756
dc.rightsDefault Licence-
dc.subjectassociative memoryen
dc.subjecthebbian learningen
dc.subjectinformation retrievalen
dc.subjectneural computationen
dc.subjectpictorial information systemsen
dc.subjectrandom neural networken
dc.subjectvisual language compileren
dc.subjectthreshold functionsen
dc.subjectcapacityen
dc.subjectsystemen
dc.titlePictorial Information-Retrieval Using the Random Neural Networken
heal.abstractA technique is developed based on the use of a neural network model for performing information retrieval in a pictorial information system. The neural network provides autoassociative memory operation and allows the retrieval of stored symbolic images using erroneous or incomplete information as input. The network used is based on an adaptation of the random neural network model featuring positive and negative nodes and symmetrical behavior of positive and negative signals. The network architecture considered here has hierarchical structure and allows two level operation during learning and recall. An experimental software prototype, including an efficient graphical interface, has been implemented and tested. The performance of the system has been investigated through experiments under several schemes concerning storage and reconstruction of patterns. These schemes are either based on properties of the random network or constitute adaptations of known neural network techniques.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.journalNameIeee Transactions on Software Engineeringen
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate1992-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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