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   <dc:title>Detection and segmentation of QR codes with arbitrary deformations</dc:title>
   <dc:creator>Latif Martínez, Hamid</dc:creator>
   <dc:subject>Àrees temàtiques de la UPC::Informàtica</dc:subject>
   <dc:subject>Computer vision</dc:subject>
   <dc:subject>Network</dc:subject>
   <dc:subject>YOLO</dc:subject>
   <dc:subject>YOLACT</dc:subject>
   <dc:subject>QR code</dc:subject>
   <dc:subject>Arbitrary Deformation</dc:subject>
   <dc:subject>YOLOv3</dc:subject>
   <dc:subject>Tiny YOLO</dc:subject>
   <dc:subject>Visió per ordinador</dc:subject>
   <dcterms:abstract>There exist classic algorithms for QR detection in photographies under certain deformations (afine, perspective, cilindrical, etc.). There are scenarios in which the deformation is arbitrary and it cannot be solved with these methods. For these, the use of neural networks is proposed to locate and decode them. This project will be focused on: detect QR codes on an image and segmentate which parts of these images correspond to these QR codes.</dcterms:abstract>
   <dcterms:issued>2020-06-30</dcterms:issued>
   <dc:type>Master thesis</dc:type>
   <dc:rights>Open Access</dc:rights>
   <dc:publisher>Universitat Politècnica de Catalunya</dc:publisher>
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