GPU-Accelerated Vision for Robots: Improving System Throughput Using OpenCV and CUDA
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INVESTIGACIONMetadatos
Título
GPU-Accelerated Vision for Robots: Improving System Throughput Using OpenCV and CUDAAutoría
Fecha de publicación
2020-06Editor
IEEECita bibliográfica
E. 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.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://ieeexplore.ieee.org/abstract/document/9047171Versión
info:eu-repo/semantics/submittedVersionPalabras clave / Materias
CUDA | GPU | OpenCV | robots | face recognition | robot vision | object identification | videos | image classification
Resumen
OpenCV 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 ... [+]
OpenCV 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. [-]
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