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Segment - based object detection and recognition

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dc.contributor Graduate Program in Electrical and Electronic Engineering.
dc.contributor.advisor Bozma, H. Işıl.
dc.contributor.author Erdem, Rabia Gökçe.
dc.date.accessioned 2023-03-16T10:19:29Z
dc.date.available 2023-03-16T10:19:29Z
dc.date.issued 2018.
dc.identifier.other EE 2018 E74
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/12932
dc.description.abstract This thesis is concerned with object detection and recognition in complex scenes. Both are necessary if robots are to be capable of interacting with their surroundings. Object detection is based on color based segmentation. Features of these segments are used in order to detect and recognize objects. A set of SVM model is constructed in the appearance space and object recognition is done based on these models. The proposed approach is evaluated experimentally in varying scenarios.
dc.format.extent 30 cm.
dc.publisher Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018.
dc.subject.lcsh Object-oriented methods (Computer science)
dc.title Segment - based object detection and recognition
dc.format.pages xiii, 64 leaves ;


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