Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Marcos V. N. Bedo"'
Autor:
Kary A. C. S. Ocaña, Marta Mattoso, Vítor Silva, Lucas Bertelli Martins, Thaylon Guedes, Marcos V. N. Bedo, Maria Luiza Falci, Daniel de Oliveira
Publikováno v:
Future Generation Computer Systems. 112:658-669
Several scientists have moved their IO- and CPU-intensive workflows to Data-Intensive Scalable Computing (DISC) frameworks aiming at benefit from high scalability, broad support, and manufacturers’ infrastructure. A prominent framework is Apache Sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f002741d2e1f6250d25cbdbc335a321d
https://doi.org/10.1016/j.future.2020.05.031
https://doi.org/10.1016/j.future.2020.05.031
Autor:
Lucio F. D. Santos, Marcos V. N. Bedo, Daniel L. Jasbick, Daniel de Oliveira, Camila R. Lopes
Publikováno v:
Journal of Information and Data Management. 12
A diversified similarity search retrieves elements that are simultaneously similar to a query object and akin to the different collections within the explored data. While several methods in information retrieval, data clustering, and similarity searc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50d0b8301d238c87d15e74e585e23de5
https://doi.org/10.5753/jidm.2021.1917
https://doi.org/10.5753/jidm.2021.1917
Autor:
Lucio F. D. Santos, Rodrigo Erthal Wilson, Renata Silva, Daniel V. Oliveira, Marcos V. N. Bedo, Davi Pereira dos Santos
Publikováno v:
SBBD
Principal component analysis (PCA) is an efficient model for the optimization problem of finding d' axes of a subspace Rd' ⊆ Rd so that the mean squared distances from a given set R of points to the axes are minimal. Despite being steadily employed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e58d508ecaa039fdf80444f97f1eba4a
https://doi.org/10.5753/sbbd.2020.13632
https://doi.org/10.5753/sbbd.2020.13632
Autor:
Marcos V. N. Bedo, Filipe Tadeu Santiago, Kary A. C. S. Ocaña, Daniel de Oliveira, Cristina Motinha, Lucas Tito
Publikováno v:
SBBD
Na última década, diversos domínios científicos vêm produzindo um grande volume de dados heterogêneos (i.e., estruturados e não-estruturados) e variantes ao longo do tempo. Apesar da popularidade, tecnologias como Data Warehouses têm se mostr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87c098cf5e1c632fb580ee6ac1cd1dd6
https://doi.org/10.5753/sbbd.2020.13633
https://doi.org/10.5753/sbbd.2020.13633
Publikováno v:
SBBD
Diversity-oriented searches retrieve objects not only similar to a reference element but also related to the different types of collections within the queried dataset. While such characterization is flexible enough to include methods originally from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a53ae9ca66dae0dc4f9cc12b19a5406b
https://doi.org/10.5753/sbbd.2020.13620
https://doi.org/10.5753/sbbd.2020.13620
Publikováno v:
Anais do Encontro de Teoria da Computação (ETC 2020).
Esse artigo apresenta uma discussão preliminar sobre o número geodésico nos grafos de Kneser. Dado um grafo G, um conjunto W,W ⊆ V (G), é dito geodesicamente convexo se qualquer vértice em algum caminho mínimo entre u e v está em W, ∀ u, v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6390d81634fbda41c1738c2df7fd87ca
https://doi.org/10.5753/etc.2020.11077
https://doi.org/10.5753/etc.2020.11077
Publikováno v:
Similarity Search and Applications ISBN: 9783030609351
SISAP
SISAP
Diversified similarity searching embeds result diversification straight into the query procedure, which boosts the computational performance by orders of magnitude. While metric indexes have a hidden potential for perfecting such procedures, the cons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e37edd152b1adb452253c18bfc7ea6a
https://doi.org/10.1007/978-3-030-60936-8_11
https://doi.org/10.1007/978-3-030-60936-8_11
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Modern Database Management Systems (DBMSs) retrieve songs that resemble those in a music dataset, identify plagiarism in a set of documents, or provide past cases to physicians by taking into account the characteristics of a query exam. All such task
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e97e4dfb6e336e3d328cd8685b6e7f7
https://doi.org/10.1016/j.datak.2017.09.003
https://doi.org/10.1016/j.datak.2017.09.003
Autor:
Daniel L. Jasbick, Wellington S. Silva, Rodrigo Erthal Wilson, Marcos V. N. Bedo, Ana Elisa Serafim Jorge, Agma J. M. Traina, Lucio F. D. Santos, Daniel de Oliveira, Paulo Mazzoncini de Azevedo-Marques
Publikováno v:
CBMS
Tissue segmentation in photographs of lower limb chronic ulcers is a non-intrusive approach that supports dermatological analyses. This paper presents 2PLA, a method that combines supervised and unsupervised learning strategies for enhancing the segm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4dcee4ac62276d7c73cc0b86b5f9e669
https://doi.org/10.1109/cbms.2019.00076
https://doi.org/10.1109/cbms.2019.00076
Autor:
Ana Elisa Serafim Jorge, Marcos V. N. Bedo, Caetano Traina, Paulo Mazzoncini de Azevedo-Marques, Agma J. M. Traina, Gustavo Blanco, Daniel de Oliveira
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Background The image-based identification of distinct tissues within dermatological wounds enhances patients’ care since it requires no intrusive evaluations. This manuscript presents an approach, we named QTDU, that combines deep learning models w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9517c993c9601fde51c92b1adcaf4971