Zobrazeno 1 - 10
of 836
pro vyhledávání: '"De Souza, P. F."'
Autor:
Duarte, D. G., de Souza, S. F., de Oliveira, L. B., Junior, E. B. M., de Araujo, E. N. D., Fonseca, J. M., de Araujo, C. I. L.
Artificial spin ices (ASI), containing magnetic monopole quasi-particles emerging at room temperature, have been investigated as a promising system to be applied in alternative low-power information technology devices. However, restrictions associate
Externí odkaz:
http://arxiv.org/abs/2406.17775
Modal decomposition techniques are important tools for the analysis of unsteady flows and, in order to provide meaningful insights with respect to coherent structures and their characteristic frequencies, the modes must possess a robust spatial suppo
Externí odkaz:
http://arxiv.org/abs/2308.12230
In this paper, we investigate the spinless stationary Schr\"odinger equation for the electron when it is permanently bound to a generalized Ellis-Bronnikov graphene wormhole-like surface. The curvature gives rise to a geometric potential affecting th
Externí odkaz:
http://arxiv.org/abs/2208.06869
Autor:
Borges, Marcelo de A., Filho, Guido L. de S., da Silva, Cicero Inacio, Barros, Anderson M. P., Britto, Raul V. B. J., Junior, Nivaldo M. de C., de Souza, Daniel F. L.
This article describes a proposal to create a digital currency that allows the decentralized collection of resources directed to initiatives and activities that aim to protect the Brazilian Amazon ecosystem by using blockchain and digital contracts.
Externí odkaz:
http://arxiv.org/abs/2203.12600
Autor:
de Mello, Jean Pablo Vieira, Paixão, Thiago M., Berriel, Rodrigo, Reyes, Mauricio, Badue, Claudine, De Souza, Alberto F., Oliveira-Santos, Thiago
Publikováno v:
In 2020 25th International Conference on Pattern Recognition (ICPR) (pp. 1-8). IEEE
The analysis of Magnetic Resonance Imaging (MRI) sequences enables clinical professionals to monitor the progression of a brain tumor. As the interest for automatizing brain volume MRI analysis increases, it becomes convenient to have each sequence w
Externí odkaz:
http://arxiv.org/abs/2106.03208
Autor:
Correia-Silva, Jacson Rodrigues, Berriel, Rodrigo F., Badue, Claudine, De Souza, Alberto F., Oliveira-Santos, Thiago
Publikováno v:
Pattern Recognition 113 (2021) 107830
Convolutional neural networks have been successful lately enabling companies to develop neural-based products, which demand an expensive process, involving data acquisition and annotation; and model generation, usually requiring experts. With all the
Externí odkaz:
http://arxiv.org/abs/2101.08717
Autor:
de Mello, Jean Pablo Vieira, Tabelini, Lucas, Berriel, Rodrigo F., Paixão, Thiago M., de Souza, Alberto F., Badue, Claudine, Sebe, Nicu, Oliveira-Santos, Thiago
Publikováno v:
Computers & Graphics (2020)
Deep neural networks come as an effective solution to many problems associated with autonomous driving. By providing real image samples with traffic context to the network, the model learns to detect and classify elements of interest, such as pedestr
Externí odkaz:
http://arxiv.org/abs/2011.03841
Autor:
Tabelini, Lucas, Berriel, Rodrigo, Paixão, Thiago M., Badue, Claudine, De Souza, Alberto F., Oliveira-Santos, Thiago
Modern lane detection methods have achieved remarkable performances in complex real-world scenarios, but many have issues maintaining real-time efficiency, which is important for autonomous vehicles. In this work, we propose LaneATT: an anchor-based
Externí odkaz:
http://arxiv.org/abs/2010.12035
Autor:
Mutz, Filipe, Oliveira-Santos, Thiago, Forechi, Avelino, Komati, Karin S., Badue, Claudine, França, Felipe M. G., De Souza, Alberto F.
The localization of self-driving cars is needed for several tasks such as keeping maps updated, tracking objects, and planning. Localization algorithms often take advantage of maps for estimating the car pose. Since maintaining and using several maps
Externí odkaz:
http://arxiv.org/abs/2009.09308
Autor:
Tabelini, Lucas, Berriel, Rodrigo, Paixão, Thiago M., De Souza, Alberto F., Badue, Claudine, Sebe, Nicu, Oliveira-Santos, Thiago
Deep learning has been successfully applied to several problems related to autonomous driving, often relying on large databases of real target-domain images for proper training. The acquisition of such real-world data is not always possible in the se
Externí odkaz:
http://arxiv.org/abs/2008.00962