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Trabalho de evento-resumo
A computational approach for image-based monitoring and morphological characterization of skin lesions (2023)
Palamoni, Otávio Perez; Moriyama, Lilian Tan
Source: Livro de Resumos. Conference titles: Semana Integrada do Instituto de Física de São Carlos - SIFSC. Unidade: IFSC
Subjects: PROCESSAMENTO DE IMAGENS, TERCEIRA DIMENSÃO (RECONSTRUÇÃO), PELE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PALAMONI, Otávio Perez e MORIYAMA, Lilian Tan. A computational approach for image-based monitoring and morphological characterization of skin lesions. 2023, Anais.. São Carlos: Instituto de Física de São Carlos - IFSC, 2023. Disponível em: https://repositorio.usp.br/directbitstream/3000c9de-3183-4a6a-998c-04d2acce76bb/PROD035529_3180139_Inserir_REP.pdf. Acesso em: 20 jan. 2026.
APA
Palamoni, O. P., & Moriyama, L. T. (2023). A computational approach for image-based monitoring and morphological characterization of skin lesions. In Livro de Resumos. São Carlos: Instituto de Física de São Carlos - IFSC. Recuperado de https://repositorio.usp.br/directbitstream/3000c9de-3183-4a6a-998c-04d2acce76bb/PROD035529_3180139_Inserir_REP.pdf
NLM
Palamoni OP, Moriyama LT. A computational approach for image-based monitoring and morphological characterization of skin lesions [Internet]. Livro de Resumos. 2023 ;[citado 2026 jan. 20 ] Available from: https://repositorio.usp.br/directbitstream/3000c9de-3183-4a6a-998c-04d2acce76bb/PROD035529_3180139_Inserir_REP.pdf
Vancouver
Palamoni OP, Moriyama LT. A computational approach for image-based monitoring and morphological characterization of skin lesions [Internet]. Livro de Resumos. 2023 ;[citado 2026 jan. 20 ] Available from: https://repositorio.usp.br/directbitstream/3000c9de-3183-4a6a-998c-04d2acce76bb/PROD035529_3180139_Inserir_REP.pdf
Artigo de periodico
An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation (2021)
Nakamura, Angelica Tiemi Mizuno ; Grassi Júnior, Valdir ; Wolf, Denis Fernando
Source: Engineering Applications of Artificial Intelligence. Unidades: EESC, ICMC
Subjects: TOMADA DE DECISÃO, ANÁLISE DE DESEMPENHO, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NAKAMURA, Angelica Tiemi Mizuno e GRASSI JÚNIOR, Valdir e WOLF, Denis Fernando. An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation. Engineering Applications of Artificial Intelligence, v. 100, p. 1-10, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.engappai.2021.104205. Acesso em: 20 jan. 2026.
APA
Nakamura, A. T. M., Grassi Júnior, V., & Wolf, D. F. (2021). An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation. Engineering Applications of Artificial Intelligence, 100, 1-10. doi:10.1016/j.engappai.2021.104205
NLM
Nakamura ATM, Grassi Júnior V, Wolf DF. An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation [Internet]. Engineering Applications of Artificial Intelligence. 2021 ; 100 1-10.[citado 2026 jan. 20 ] Available from: https://doi.org/10.1016/j.engappai.2021.104205
Vancouver
Nakamura ATM, Grassi Júnior V, Wolf DF. An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation [Internet]. Engineering Applications of Artificial Intelligence. 2021 ; 100 1-10.[citado 2026 jan. 20 ] Available from: https://doi.org/10.1016/j.engappai.2021.104205
Dissertação (Mestrado)
Environment reconstruction on disparity images using surface features and Generative Adversarial Networks (2020)
Matias, Lucas Peres Nunes; Wolf, Denis Fernando (Orientador)
Unidade: ICMC
Subjects: VEÍCULOS AUTÔNOMOS, PROCESSAMENTO DE IMAGENS, SEGURANÇA NO TRÂNSITO, VISÃO COMPUTACIONAL, ROBÓTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MATIAS, Lucas Peres Nunes. Environment reconstruction on disparity images using surface features and Generative Adversarial Networks. 2020. Dissertação (Mestrado) – Universidade de São Paulo, São Carlos, 2020. Disponível em: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27072020-163017/. Acesso em: 20 jan. 2026.
APA
Matias, L. P. N. (2020). Environment reconstruction on disparity images using surface features and Generative Adversarial Networks (Dissertação (Mestrado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27072020-163017/
NLM
Matias LPN. Environment reconstruction on disparity images using surface features and Generative Adversarial Networks [Internet]. 2020 ;[citado 2026 jan. 20 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27072020-163017/
Vancouver
Matias LPN. Environment reconstruction on disparity images using surface features and Generative Adversarial Networks [Internet]. 2020 ;[citado 2026 jan. 20 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27072020-163017/

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