Intelligent action-based image recognition system

Alexopoulos, Vassilios; Kollias, Stefanos

dc.contributor.author	Alexopoulos, Vassilios	en
dc.contributor.author	Kollias, Stefanos	en
dc.date.accessioned	2014-03-01T01:44:45Z
dc.date.available	2014-03-01T01:44:45Z
dc.date.issued	1996	en
dc.identifier.issn	12100552	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/24474
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0029719145&partnerID=40&md5=d6e3796d9fbc906549df8322cd16677e	en
dc.subject.other	Feature extraction	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Image processing	en
dc.subject.other	Pattern recognition	en
dc.subject.other	Spurious signal noise	en
dc.subject.other	Vision	en
dc.subject.other	Fuzzy subsystem	en
dc.subject.other	Intelligent action based image recognition system	en
dc.subject.other	Neural network classifier	en
dc.subject.other	Visual information processing	en
dc.subject.other	Neural networks	en
dc.title	Intelligent action-based image recognition system	en
heal.type	journalArticle	en
heal.publicationDate	1996	en
heal.abstract	This paper presents a novel intelligent system for recognition of images or scenes, which includes neural network architectures and is inspired by human perception actions. In particular, a recurrent neural network subsystem is used to extract features from the images; these features being associated to the way humans perceive visual information. A neural network classifier, followed by a fuzzy subsystem, is used for interpretation of the extracted features. Results are presented using images of objects, that are deformed and/or corrupted by noise, which illustrate the capabilities of the proposed system.	en
heal.publisher	IDG, Prague, Czech Republic	en
heal.journalName	Neural Network World	en
dc.identifier.volume	6	en
dc.identifier.issue	3	en
dc.identifier.spage	251	en
dc.identifier.epage	258	en