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dc.contributor.authorSANTOS, T. T.pt_BR
dc.date.accessioned2015-05-19T11:11:11Zpt_BR
dc.date.available2015-05-19T11:11:11Zpt_BR
dc.date.created2015-05-19pt_BR
dc.date.issued2015pt_BR
dc.identifier.citationRevista de Informática Teórica e Aplicada, v. 22, n. 1, p. 154-189, 2015.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1015739pt_BR
dc.descriptionIn research and development (R&D), interactive computing environments are a frequently employed alternative for data exploration, algorithm development and prototyping. In the last twelve years, a popular scientific computing environment flourished around the Python programming language. Most of this environment is part of (or built over) a software stack named SciPy Stack. Combined with OpenCV?s Python interface, this environment becomes an alternative for current computer vision R&D. This tutorial introduces such an environment and shows how it can address different steps of computer vision research, from initial data exploration to parallel computing implementations. Several code examples are presented. They deal with problems from simple image processing to inference by machine learning. All examples are also available as IPython notebooks.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectComputaçãopt_BR
dc.titleSciPy and OpenCV as an interactive computing environment for computer vision.pt_BR
dc.typeArtigo de periódicopt_BR
dc.date.updated2016-02-22T11:11:11Zpt_BR
dc.subject.nalthesaurusComputer visionpt_BR
dc.subject.nalthesaurusDigital imagespt_BR
dc.subject.nalthesaurusImage analysispt_BR
riaa.ainfo.id1015739pt_BR
riaa.ainfo.lastupdate2016-02-22pt_BR
dc.contributor.institutionTHIAGO TEIXEIRA SANTOS, CNPTIA.pt_BR
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