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dc.contributor.advisorOsorio, Fernando Santos
dc.contributor.authorBender, Túlio Cléberpt_BR
dc.date.accessioned2015-03-05T13:53:43Z
dc.date.accessioned2022-09-22T19:05:04Z
dc.date.available2015-03-05T13:53:43Z
dc.date.available2022-09-22T19:05:04Z
dc.date.issued2003-07-24
dc.identifier.urihttps://hdl.handle.net/20.500.12032/56733
dc.description.abstractImage retrieval and classification are today the subject of extensive research. This topic poses both theoretical and practical challenges as researchers attempt to give machines such as computers and robots the ability to “see”. Image retrieval and classification are part of a wider field known as Computer Vision, which encompasses several practical applications such as image retrieval from databases storing only raw images, biometric recognition (from images of finger-prints, face or iris), retrieval of visual trademarks and logos from advertisements, location of objects in a scene and vision techniques in robotics. The research developed in this work is focused on obtaining a generalization of characteristics extracted from a collection of images belonging to a single class using supervised learning techniques. The result is a model that “identifies” a given class of images. To achieve this, a review of the state-of-the-art in content-based image retrieval systems and Machine Learning techniques was needeen
dc.description.sponsorshipNenhumapt_BR
dc.languagept_BRpt_BR
dc.publisherUniversidade do Vale do Rio do Sinospt_BR
dc.rightsopenAccesspt_BR
dc.subjectclassificação de imagenspt_BR
dc.subjectclosed separation surfacesen
dc.titleClassificação e recuperação de imagens por cor utilizando técnicas de inteligência artificialpt_BR
dc.typeDissertaçãopt_BR


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