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Artigo de periodico
A comparison among keyframe extraction techniques for CNN classification based on video periocular images (2021)
Ferraz, Carolina Toledo ; Barcellos, William; Pereira Junior, Osmando ; Borges, Tamiris Trevisan Negri ; Manzato, Marcelo Garcia ; Gonzaga, Adilson ; Saito, Jose Hiroki
Source: Multimedia Tools and Applications. Unidades: ICMC, EESC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, OLHO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERRAZ, Carolina Toledo et al. A comparison among keyframe extraction techniques for CNN classification based on video periocular images. Multimedia Tools and Applications, v. 80, n. 8, p. 12843-12856, 2021Tradução . . Disponível em: https://doi.org/10.1007/s11042-020-10384-9. Acesso em: 02 jun. 2024.
APA
Ferraz, C. T., Barcellos, W., Pereira Junior, O., Borges, T. T. N., Manzato, M. G., Gonzaga, A., & Saito, J. H. (2021). A comparison among keyframe extraction techniques for CNN classification based on video periocular images. Multimedia Tools and Applications, 80( 8), 12843-12856. doi:10.1007/s11042-020-10384-9
NLM
Ferraz CT, Barcellos W, Pereira Junior O, Borges TTN, Manzato MG, Gonzaga A, Saito JH. A comparison among keyframe extraction techniques for CNN classification based on video periocular images [Internet]. Multimedia Tools and Applications. 2021 ; 80( 8): 12843-12856.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1007/s11042-020-10384-9
Vancouver
Ferraz CT, Barcellos W, Pereira Junior O, Borges TTN, Manzato MG, Gonzaga A, Saito JH. A comparison among keyframe extraction techniques for CNN classification based on video periocular images [Internet]. Multimedia Tools and Applications. 2021 ; 80( 8): 12843-12856.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1007/s11042-020-10384-9
Trabalho de evento
Impact of facial expressions on the accuracy of a CNN performing periocular recognition (2019)
Dalapicola, Rodolfo Coelho; Queiroga, Raissa Tavares Vieira; Ferraz, Carolina Toledo; Borges, Tamiris Trevisan Negri; Saito, Jose Hiroki; Gonzaga, Adilson
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: EESC
Subjects: BIOMETRIA, REDES NEURAIS, TRANSFERÊNCIA (APRENDIZAGEM), ENGENHARIA ELÉTRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DALAPICOLA, Rodolfo Coelho et al. Impact of facial expressions on the accuracy of a CNN performing periocular recognition. 2019, Anais.. Piscataway, NJ, USA: IEEE, 2019. Disponível em: https://doi.org/10.1109/BRACIS.2019.00077. Acesso em: 02 jun. 2024.
APA
Dalapicola, R. C., Queiroga, R. T. V., Ferraz, C. T., Borges, T. T. N., Saito, J. H., & Gonzaga, A. (2019). Impact of facial expressions on the accuracy of a CNN performing periocular recognition. In Proceedings. Piscataway, NJ, USA: IEEE. doi:10.1109/BRACIS.2019.00077
NLM
Dalapicola RC, Queiroga RTV, Ferraz CT, Borges TTN, Saito JH, Gonzaga A. Impact of facial expressions on the accuracy of a CNN performing periocular recognition [Internet]. Proceedings. 2019 ;[citado 2024 jun. 02 ] Available from: https://doi.org/10.1109/BRACIS.2019.00077
Vancouver
Dalapicola RC, Queiroga RTV, Ferraz CT, Borges TTN, Saito JH, Gonzaga A. Impact of facial expressions on the accuracy of a CNN performing periocular recognition [Internet]. Proceedings. 2019 ;[citado 2024 jun. 02 ] Available from: https://doi.org/10.1109/BRACIS.2019.00077
Trabalho de evento
Evaluation of convolutional neural networks for raw food texture classification under variations of lighting conditions (2018)
Ferraz, Carolina Toledo ; Borges, Tamiris Trevisan Negri ; Cavichiolli, Adriane; Gonzaga, Adilson ; Saito, Jose Hiroki
Source: Proceedings. Conference titles: Conference on Graphics, Patterns and Images- SIBGRAPI. Unidade: EESC
Subjects: REDES NEURAIS, ILUMINAÇÃO, ALIMENTOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERRAZ, Carolina Toledo et al. Evaluation of convolutional neural networks for raw food texture classification under variations of lighting conditions. 2018, Anais.. Porto Alegre: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2018. Disponível em: https://repositorio.usp.br/directbitstream/b8ee5039-0201-4853-a7af-c70ad283e3c9/sysno3190748_trabalho%2008%20-%20Evaluation%20of%20convolutional%20neural%20networks%20for%20raw%20food%20texture%20classification%20under%20variations%20of%20lighting%20conditions.%20%28SIBGRAPI%2C%202018%29.pdf. Acesso em: 02 jun. 2024.
APA
Ferraz, C. T., Borges, T. T. N., Cavichiolli, A., Gonzaga, A., & Saito, J. H. (2018). Evaluation of convolutional neural networks for raw food texture classification under variations of lighting conditions. In Proceedings. Porto Alegre: Escola de Engenharia de São Carlos, Universidade de São Paulo. Recuperado de https://repositorio.usp.br/directbitstream/b8ee5039-0201-4853-a7af-c70ad283e3c9/sysno3190748_trabalho%2008%20-%20Evaluation%20of%20convolutional%20neural%20networks%20for%20raw%20food%20texture%20classification%20under%20variations%20of%20lighting%20conditions.%20%28SIBGRAPI%2C%202018%29.pdf
NLM
Ferraz CT, Borges TTN, Cavichiolli A, Gonzaga A, Saito JH. Evaluation of convolutional neural networks for raw food texture classification under variations of lighting conditions [Internet]. Proceedings. 2018 ;[citado 2024 jun. 02 ] Available from: https://repositorio.usp.br/directbitstream/b8ee5039-0201-4853-a7af-c70ad283e3c9/sysno3190748_trabalho%2008%20-%20Evaluation%20of%20convolutional%20neural%20networks%20for%20raw%20food%20texture%20classification%20under%20variations%20of%20lighting%20conditions.%20%28SIBGRAPI%2C%202018%29.pdf
Vancouver
Ferraz CT, Borges TTN, Cavichiolli A, Gonzaga A, Saito JH. Evaluation of convolutional neural networks for raw food texture classification under variations of lighting conditions [Internet]. Proceedings. 2018 ;[citado 2024 jun. 02 ] Available from: https://repositorio.usp.br/directbitstream/b8ee5039-0201-4853-a7af-c70ad283e3c9/sysno3190748_trabalho%2008%20-%20Evaluation%20of%20convolutional%20neural%20networks%20for%20raw%20food%20texture%20classification%20under%20variations%20of%20lighting%20conditions.%20%28SIBGRAPI%2C%202018%29.pdf

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