Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Lucas Pascotti Valem"'
Autor:
Filipe Alves de Fernando, Daniel Carlos Guimarães Pedronette, Gustavo José de Sousa, Lucas Pascotti Valem, Ivan Rizzo Guilherme
Publikováno v:
International Journal of Information Management Data Insights, Vol 2, Iss 1, Pp 100078- (2022)
Due to the possibility of capturing complex relationships existing between nodes, many applications benefit from being modeled with graphs. However, performance issues can be observed in large-scale networks, making it computationally unfeasible to p
Externí odkaz:
https://doaj.org/article/b4373281103d4cd588bb4e473f34813f
Publikováno v:
Journal of Imaging, Vol 7, Iss 3, p 49 (2021)
Visual features and representation learning strategies experienced huge advances in the previous decade, mainly supported by deep learning approaches. However, retrieval tasks are still performed mainly based on traditional pairwise dissimilarity mea
Externí odkaz:
https://doaj.org/article/dbc5714a31ef4a618c79eec0a02f8e56
Publikováno v:
IEEE Transactions on Image Processing. 32:2811-2826
Impressive advances in acquisition and sharing technologies have made the growth of multimedia collections and their applications almost unlimited. However, the opposite is true for the availability of labeled data, which is needed for supervised tra
Autor:
Claudio Filipi Gonçalves dos Santos, Diego de Souza Oliveira, Leandro A. Passos, Rafael Gonçalves Pires, Daniel Felipe Silva Santos, Lucas Pascotti Valem, Thierry P. Moreira, Marcos Cleison S. Santana, Mateus Roder, Jo Paulo Papa, Danilo Colombo
Publikováno v:
ACM Computing Surveys. 55:1-34
In general, biometry-based control systems may not rely on individual expected behavior or cooperation to operate appropriately. Instead, such systems should be aware of malicious procedures for unauthorized access attempts. Some works available in t
Due to a huge volume of information in many domains, the need for classification methods is imperious. In spite of many advances, most of the approaches require a large amount of labeled data, which is often not available, due to costs and difficulti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16d1d7df4091c5b3bd6ff059e9b4eafd
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP).
Publikováno v:
Expert Systems with Applications. 213:118995
Publikováno v:
Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Made available in DSpace on 2020-12-12T01:23:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-07-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Nowa
Publikováno v:
Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Made available in DSpace on 2020-12-12T01:44:19Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-02-15 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Seve
Autor:
Lucas Pascotti Valem, Daniel Carlos Guimarães Pedronette, Jurandy Almeida, Ricardo da Silva Torres
Publikováno v:
Web of Science
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Made available in DSpace on 2019-10-04T12:41:35Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-12-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coor