Semantic adaptation of neural network classifiers in image segmentation

Simou, N; Athanasiadis, T; Kollias, S; Stamou, G; Stafylopatis, A

dc.contributor.author	Simou, N	en
dc.contributor.author	Athanasiadis, T	en
dc.contributor.author	Kollias, S	en
dc.contributor.author	Stamou, G	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T02:45:47Z
dc.date.available	2014-03-01T02:45:47Z
dc.date.issued	2008	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32387
dc.subject	Fuzzy Reasoning	en
dc.subject	Image Segmentation	en
dc.subject	Knowledge Base	en
dc.subject	Machine Learning	en
dc.subject	Neural Network Classifier	en
dc.subject	Semantic Analysis	en
dc.subject	Confidence Level	en
dc.subject.other	Confidence levels	en
dc.subject.other	Fuzzy reasoning	en
dc.subject.other	Knowledge base	en
dc.subject.other	Machine learning techniques	en
dc.subject.other	Multi-media analysis	en
dc.subject.other	Multimedia contents	en
dc.subject.other	Network classifiers	en
dc.subject.other	Neural network classifier	en
dc.subject.other	Research areas	en
dc.subject.other	Semantic adaptation	en
dc.subject.other	Semantic analysis	en
dc.subject.other	Backpropagation	en
dc.subject.other	Classifiers	en
dc.subject.other	Digital image storage	en
dc.subject.other	Image segmentation	en
dc.subject.other	Knowledge based systems	en
dc.subject.other	Learning algorithms	en
dc.subject.other	Learning systems	en
dc.subject.other	Multimedia systems	en
dc.subject.other	Semantics	en
dc.subject.other	Neural networks	en
dc.title	Semantic adaptation of neural network classifiers in image segmentation	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-540-87536-9_93	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-87536-9_93	en
heal.publicationDate	2008	en
heal.abstract	Semantic analysis of multimedia content is an on going research area that has gained a lot of attention over the last few years. Additionally, machine learning techniques are widely used for multimedia analysis with great success. This work presents a combined approach to semantic adaptation of neural network classifiers in multimedia framework. It is based on a fuzzy reasoning engine which is able to evaluate the outputs and the confidence levels of the neural network classifier, using a knowledge base. Improved image segmentation results are obtained, which are used for adaptation of the network classifier, further increasing its ability to provide accurate classification of the specific content. © Springer-Verlag Berlin Heidelberg 2008.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-540-87536-9_93	en
dc.identifier.volume	5163 LNCS	en
dc.identifier.issue	PART 1	en
dc.identifier.spage	907	en
dc.identifier.epage	916	en