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dc.contributor.authorCervera, Enric
dc.date.accessioned2020-09-02T06:34:02Z
dc.date.available2020-09-02T06:34:02Z
dc.date.issued2020-06
dc.identifier.citationE. Cervera, "GPU-Accelerated Vision for Robots: Improving System Throughput Using OpenCV and CUDA," in IEEE Robotics & Automation Magazine, vol. 27, no. 2, pp. 151-158, June 2020, doi: 10.1109/MRA.2020.2977601.ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/189456
dc.description.abstractOpenCV is an open source computer vision and machine learning library for C/C++/Python available for Windows, Linux, macOS, and Android platforms. It contains low-level image processing functions as well as high-level algorithms such as object identification, face recognition, and action classification in videos. OpenCV has become very popular, with more than 47,000 people in its user community and 18 million downloads (see https://opencv.org/about/). Under a Berkeley Software Distribution (BSD) license, it can be used for both academic and commercial applications.ca_CA
dc.format.extent7 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherIEEEca_CA
dc.rights© Copyright 2020 IEEE - All rights reserved.ca_CA
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/*
dc.subjectCUDAca_CA
dc.subjectGPUca_CA
dc.subjectOpenCVca_CA
dc.subjectrobotsca_CA
dc.subjectface recognitionca_CA
dc.subjectrobot visionca_CA
dc.subjectobject identificationca_CA
dc.subjectvideosca_CA
dc.subjectimage classificationca_CA
dc.titleGPU-Accelerated Vision for Robots: Improving System Throughput Using OpenCV and CUDAca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1109/MRA.2020.2977601
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://ieeexplore.ieee.org/abstract/document/9047171ca_CA
dc.type.versioninfo:eu-repo/semantics/submittedVersionca_CA


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