Zobrazeno 1 - 10
of 631
pro vyhledávání: '"da Silva Vinícius"'
Earth structural heterogeneities have a remarkable role in the petroleum economy for both exploration and production projects. Automatic detection of detailed structural heterogeneities is challenging when considering modern machine learning techniqu
Externí odkaz:
http://arxiv.org/abs/2404.10170
Autor:
Schardong, Guilherme, Novello, Tiago, Paz, Hallison, Medvedev, Iurii, da Silva, Vinícius, Velho, Luiz, Gonçalves, Nuno
Face morphing is a problem in computer graphics with numerous artistic and forensic applications. It is challenging due to variations in pose, lighting, gender, and ethnicity. This task consists of a warping for feature alignment and a blending for a
Externí odkaz:
http://arxiv.org/abs/2308.13888
Automatic Text Summarization (ATS) is becoming relevant with the growth of textual data; however, with the popularization of public large-scale datasets, some recent machine learning approaches have focused on dense models and architectures that, des
Externí odkaz:
http://arxiv.org/abs/2212.10707
Autor:
da Silva, Vinícius Barros1 (AUTHOR) edson-denis.leonel@unesp.br, Vieira, João Peres2 (AUTHOR) joao.peres@unesp.br, Leonel, Edson Denis1 (AUTHOR)
Publikováno v:
Entropy. Sep2024, Vol. 26 Issue 9, p745. 73p.
Autor:
Silva, Marília Costa Rosendo, Siqueira, Felipe Alves, Tarrega, João Pedro Mantovani, Beinotti, João Vitor Pataca, Nunes, Augusto Sousa, Gardini, Miguel de Mattos, da Silva, Vinícius Adolfo Pereira, da Silva, Nádia Félix Felipe, de Carvalho, André Carlos Ponce de Leon Ferreira
Extracting knowledge from unlabeled texts using machine learning algorithms can be complex. Document categorization and information retrieval are two applications that may benefit from unsupervised learning (e.g., text clustering and topic modeling),
Externí odkaz:
http://arxiv.org/abs/2208.01712
Autor:
Oliveira da Silva, Vinícius, Galdino dos Santos, Fabio, Diniz, Isis Nóbile, Lacerda Baitelo, Ricardo, Ferreira, André Luis
Publikováno v:
In Renewable and Sustainable Energy Reviews October 2024 203
Autor:
Novello, Tiago, da Silva, Vinicius, Schardong, Guilherme, Schirmer, Luiz, Lopes, Helio, Velho, Luiz
This work investigates the use of smooth neural networks for modeling dynamic variations of implicit surfaces under the level set equation (LSE). For this, it extends the representation of neural implicit surfaces to the space-time $\mathbb{R}^3\time
Externí odkaz:
http://arxiv.org/abs/2201.09636
Autor:
Novello, Tiago, Schardong, Guilherme, Schirmer, Luiz, da Silva, Vinicius, Lopes, Helio, Velho, Luiz
We introduce a neural implicit framework that exploits the differentiable properties of neural networks and the discrete geometry of point-sampled surfaces to approximate them as the level sets of neural implicit functions. To train a neural implicit
Externí odkaz:
http://arxiv.org/abs/2201.09263
Autor:
da Silva, Vinícius, Novello, Tiago, Schardong, Guilherme, Schirmer, Luiz, Lopes, Hélio, Velho, Luiz
We introduce a novel approach for rendering static and dynamic 3D neural signed distance functions (SDF) in real-time. We rely on nested neighborhoods of zero-level sets of neural SDFs, and mappings between them. This framework supports animations an
Externí odkaz:
http://arxiv.org/abs/2201.09147
Autor:
Correia Bulhões, Lidiane Cristina, Alves Gomes, Sâmara Raquel, da Silva, Vinícius Dantas, de Azevedo Rodolfo, Jully Israely, Macedo, Liane de Brito, Brasileiro, Jamilson Simões
Publikováno v:
In Journal of Bodywork & Movement Therapies July 2024 39:544-549