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  • Source: Multimedia Tools and Applications. Unidades: STI, IME, EACH

    Subjects: SEGURANÇA PÚBLICA, GRAVAÇÃO DE VÍDEO

    Disponível em 2024-06-20Acesso à fonteDOIHow to cite
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      GONCALVES, Vinicius P. M. et al. Concept drift adaptation in video surveillance: a systematic review. Multimedia Tools and Applications, v. 83, n. 4, p. 9997-10037, 2024Tradução . . Disponível em: https://doi.org/10.1007/s11042-023-15855-3. Acesso em: 26 abr. 2024.
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      Goncalves, V. P. M., Silva, L. P., Marques, F. de L. dos S. N., Ferreira, J. E., & Araújo, L. V. de. (2024). Concept drift adaptation in video surveillance: a systematic review. Multimedia Tools and Applications, 83( 4), 9997-10037. doi:10.1007/s11042-023-15855-3
    • NLM

      Goncalves VPM, Silva LP, Marques F de L dos SN, Ferreira JE, Araújo LV de. Concept drift adaptation in video surveillance: a systematic review [Internet]. Multimedia Tools and Applications. 2024 ; 83( 4): 9997-10037.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-15855-3
    • Vancouver

      Goncalves VPM, Silva LP, Marques F de L dos SN, Ferreira JE, Araújo LV de. Concept drift adaptation in video surveillance: a systematic review [Internet]. Multimedia Tools and Applications. 2024 ; 83( 4): 9997-10037.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-15855-3
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, NEOPLASIAS CUTÂNEAS

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      SPOLAÔR, Newton et al. Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets. Multimedia Tools and Applications, v. 83, n. 9, p. 27305-27329, 2024Tradução . . Disponível em: https://doi.org/10.1007/s11042-023-16529-w. Acesso em: 26 abr. 2024.
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      Spolaôr, N., Lee, H. D., Mendes, A. I., Nogueira, C. V., Parmezan, A. R. S., Takaki, W. S. R., et al. (2024). Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets. Multimedia Tools and Applications, 83( 9), 27305-27329. doi:10.1007/s11042-023-16529-w
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      Spolaôr N, Lee HD, Mendes AI, Nogueira CV, Parmezan ARS, Takaki WSR, Coy CSR, Wu FC, Fonseca-Pinto R. Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets [Internet]. Multimedia Tools and Applications. 2024 ; 83( 9): 27305-27329.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-16529-w
    • Vancouver

      Spolaôr N, Lee HD, Mendes AI, Nogueira CV, Parmezan ARS, Takaki WSR, Coy CSR, Wu FC, Fonseca-Pinto R. Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets [Internet]. Multimedia Tools and Applications. 2024 ; 83( 9): 27305-27329.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-16529-w
  • Source: Multimedia Tools and Applications. Unidade: EACH

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      SANCHES, Silvio Ricardo Rodrigues et al. Automatic generation of difficulty maps for datasets using neural network. Multimedia Tools and Applications, n. Ja 2024, p. 01-18, 2024Tradução . . Disponível em: http://dx.doi.org/10.1007/s11042-024-18271-3. Acesso em: 26 abr. 2024.
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      Sanches, S. R. R., Custódio Junior, E., Corrêa, C. G., Oliveira, C., Silva, V. F. da, Saito, P. T. M., & Bugatti, P. H. (2024). Automatic generation of difficulty maps for datasets using neural network. Multimedia Tools and Applications, ( Ja 2024), 01-18. doi:10.1007/s11042-024-18271-3
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      Sanches SRR, Custódio Junior E, Corrêa CG, Oliveira C, Silva VF da, Saito PTM, Bugatti PH. Automatic generation of difficulty maps for datasets using neural network [Internet]. Multimedia Tools and Applications. 2024 ;( Ja 2024): 01-18.[citado 2024 abr. 26 ] Available from: http://dx.doi.org/10.1007/s11042-024-18271-3
    • Vancouver

      Sanches SRR, Custódio Junior E, Corrêa CG, Oliveira C, Silva VF da, Saito PTM, Bugatti PH. Automatic generation of difficulty maps for datasets using neural network [Internet]. Multimedia Tools and Applications. 2024 ;( Ja 2024): 01-18.[citado 2024 abr. 26 ] Available from: http://dx.doi.org/10.1007/s11042-024-18271-3
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: ANÁLISE DE SÉRIES TEMPORAIS, VISUALIZAÇÃO, RECURSOS HÍDRICOS, CLIMA

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      BYBORDI, Arezoo et al. Canonical correlation and visual analytics for water resources analysis. Multimedia Tools and Applications, v. 83, n. 11, p. 32453-32473, 2024Tradução . . Disponível em: https://doi.org/10.1007/s11042-023-16926-1. Acesso em: 26 abr. 2024.
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      Bybordi, A., Thampan, T., Linhares, C. D. G., Ponciano, J. R., Travençolo, B. A. N., Paiva, J. G. de S., & Etemadpour, R. (2024). Canonical correlation and visual analytics for water resources analysis. Multimedia Tools and Applications, 83( 11), 32453-32473. doi:10.1007/s11042-023-16926-1
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      Bybordi A, Thampan T, Linhares CDG, Ponciano JR, Travençolo BAN, Paiva JG de S, Etemadpour R. Canonical correlation and visual analytics for water resources analysis [Internet]. Multimedia Tools and Applications. 2024 ; 83( 11): 32453-32473.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-16926-1
    • Vancouver

      Bybordi A, Thampan T, Linhares CDG, Ponciano JR, Travençolo BAN, Paiva JG de S, Etemadpour R. Canonical correlation and visual analytics for water resources analysis [Internet]. Multimedia Tools and Applications. 2024 ; 83( 11): 32453-32473.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-16926-1
  • Source: Multimedia Tools and Applications. Unidades: IRI, EACH

    Subjects: INDÚSTRIA CINEMATOGRÁFICA, PRODUÇÃO CINEMATOGRÁFICA, APRENDIZADO COMPUTACIONAL, SUCESSO NOS NEGÓCIOS

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      SOUZA, Thais Luiza Donega e e NISHIJIMA, Marislei e PIRES, Ricardo. Revisiting predictions of movie economic success: random Forest applied to profits. Multimedia Tools and Applications, p. 1-24, 2023Tradução . . Disponível em: https://doi.org/10.1007/s11042-023-15169-4. Acesso em: 26 abr. 2024.
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      Souza, T. L. D. e, Nishijima, M., & Pires, R. (2023). Revisiting predictions of movie economic success: random Forest applied to profits. Multimedia Tools and Applications, 1-24. doi:10.1007/s11042-023-15169-4
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      Souza TLD e, Nishijima M, Pires R. Revisiting predictions of movie economic success: random Forest applied to profits [Internet]. Multimedia Tools and Applications. 2023 ; 1-24.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-15169-4
    • Vancouver

      Souza TLD e, Nishijima M, Pires R. Revisiting predictions of movie economic success: random Forest applied to profits [Internet]. Multimedia Tools and Applications. 2023 ; 1-24.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-15169-4
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM, REDES NEURAIS, APRENDIZADO COMPUTACIONAL

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      RIBEIRO, Leo Sampaio Ferraz et al. Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task. Multimedia Tools and Applications, v. 82, n. 24, p. 38117-38139, 2023Tradução . . Disponível em: https://doi.org/10.1007/s11042-022-14282-0. Acesso em: 26 abr. 2024.
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      Ribeiro, L. S. F., Bui, T., Collomosse, J., & Ponti, M. A. (2023). Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task. Multimedia Tools and Applications, 82( 24), 38117-38139. doi:10.1007/s11042-022-14282-0
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      Ribeiro LSF, Bui T, Collomosse J, Ponti MA. Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task [Internet]. Multimedia Tools and Applications. 2023 ; 82( 24): 38117-38139.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-022-14282-0
    • Vancouver

      Ribeiro LSF, Bui T, Collomosse J, Ponti MA. Scene designer: compositional sketch-based image retrieval with contrastive learning and an auxiliary synthesis task [Internet]. Multimedia Tools and Applications. 2023 ; 82( 24): 38117-38139.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-022-14282-0
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: MULTIMÍDIA, RECONHECIMENTO DE IMAGEM, VÍDEO

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      BESERRA, Antonio Alessandro Rocha e GOULARTE, Rudinei. Multimodal early fusion operators for temporal video scene segmentation tasks. Multimedia Tools and Applications, v. 82, n. 20, p. 31539-31556, 2023Tradução . . Disponível em: https://doi.org/10.1007/s11042-023-14953-6. Acesso em: 26 abr. 2024.
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      Beserra, A. A. R., & Goularte, R. (2023). Multimodal early fusion operators for temporal video scene segmentation tasks. Multimedia Tools and Applications, 82( 20), 31539-31556. doi:10.1007/s11042-023-14953-6
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      Beserra AAR, Goularte R. Multimodal early fusion operators for temporal video scene segmentation tasks [Internet]. Multimedia Tools and Applications. 2023 ; 82( 20): 31539-31556.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-14953-6
    • Vancouver

      Beserra AAR, Goularte R. Multimodal early fusion operators for temporal video scene segmentation tasks [Internet]. Multimedia Tools and Applications. 2023 ; 82( 20): 31539-31556.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-023-14953-6
  • Source: Multimedia Tools and Applications. Unidade: EACH

    Assunto: REABILITAÇÃO

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      ARANHA, Renan Vinicius et al. EasyAffecta: a framework to develop serious games for virtual rehabilitation with affective adaptation. Multimedia Tools and Applications, v. 82, p. 2303-2328, 2023Tradução . . Disponível em: https://doi.org/10.1007/s11042-022-12600-0. Acesso em: 26 abr. 2024.
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      Aranha, R. V., Chaim, M. L., Monteiro, C. B. de M., Silva, T. D., Guerreiro, F. A. A. de C., Silva, W. S., & Marques, F. de L. dos S. N. (2023). EasyAffecta: a framework to develop serious games for virtual rehabilitation with affective adaptation. Multimedia Tools and Applications, 82, 2303-2328. doi:10.1007/s11042-022-12600-0
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      Aranha RV, Chaim ML, Monteiro CB de M, Silva TD, Guerreiro FAA de C, Silva WS, Marques F de L dos SN. EasyAffecta: a framework to develop serious games for virtual rehabilitation with affective adaptation [Internet]. Multimedia Tools and Applications. 2023 ; 82 2303-2328.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-022-12600-0
    • Vancouver

      Aranha RV, Chaim ML, Monteiro CB de M, Silva TD, Guerreiro FAA de C, Silva WS, Marques F de L dos SN. EasyAffecta: a framework to develop serious games for virtual rehabilitation with affective adaptation [Internet]. Multimedia Tools and Applications. 2023 ; 82 2303-2328.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-022-12600-0
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: VISÃO COMPUTACIONAL, ENCHENTES URBANAS, SEMÂNTICA

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      FERNANDES JUNIOR, Francisco Erivaldo e NONATO, Luis Gustavo e UEYAMA, Jó. A river flooding detection system based on deep learning and computer vision. Multimedia Tools and Applications, v. 81, p. 40231-40251, 2022Tradução . . Disponível em: https://doi.org/10.1007/s11042-022-12813-3. Acesso em: 26 abr. 2024.
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      Fernandes Junior, F. E., Nonato, L. G., & Ueyama, J. (2022). A river flooding detection system based on deep learning and computer vision. Multimedia Tools and Applications, 81, 40231-40251. doi:10.1007/s11042-022-12813-3
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      Fernandes Junior FE, Nonato LG, Ueyama J. A river flooding detection system based on deep learning and computer vision [Internet]. Multimedia Tools and Applications. 2022 ; 81 40231-40251.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-022-12813-3
    • Vancouver

      Fernandes Junior FE, Nonato LG, Ueyama J. A river flooding detection system based on deep learning and computer vision [Internet]. Multimedia Tools and Applications. 2022 ; 81 40231-40251.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-022-12813-3
  • Source: Multimedia Tools and Applications. Unidades: EACH, EP

    Assunto: JOGOS

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      ARANHA, Renan Vinicius et al. EasyAffecta: a framework to develop serious games for virtual rehabilitation with affective adaptation. Multimedia Tools and Applications, p. 01-16, 2022Tradução . . Disponível em: https://doi.org/10.1007/s11042-022-12600-0. Acesso em: 26 abr. 2024.
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      Aranha, R. V., Chaim, M. L., Monteiro, C. B. de M., Silva, T. D., Guerreiro, F. A. A. de C., Silva, W. S. da, & Marques, F. de L. dos S. N. (2022). EasyAffecta: a framework to develop serious games for virtual rehabilitation with affective adaptation. Multimedia Tools and Applications, 01-16. doi:10.1007/s11042-022-12600-0
    • NLM

      Aranha RV, Chaim ML, Monteiro CB de M, Silva TD, Guerreiro FAA de C, Silva WS da, Marques F de L dos SN. EasyAffecta: a framework to develop serious games for virtual rehabilitation with affective adaptation [Internet]. Multimedia Tools and Applications. 2022 ; 01-16.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-022-12600-0
    • Vancouver

      Aranha RV, Chaim ML, Monteiro CB de M, Silva TD, Guerreiro FAA de C, Silva WS da, Marques F de L dos SN. EasyAffecta: a framework to develop serious games for virtual rehabilitation with affective adaptation [Internet]. Multimedia Tools and Applications. 2022 ; 01-16.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-022-12600-0
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE VOZ, PROCESSAMENTO DE LINGUAGEM NATURAL, VÍDEO

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      SPOLAÔR, Newton et al. A video indexing and retrieval computational prototype based on transcribed speech. Multimedia Tools and Applications, v. 80, n. 5, p. 33971-34017, 2021Tradução . . Disponível em: https://doi.org/10.1007/s11042-021-11401-1. Acesso em: 26 abr. 2024.
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      Spolaôr, N., Lee, H. D., Takaki, W. S. R., Ensina, L. A., Parmezan, A. R. S., Oliva, J. T., et al. (2021). A video indexing and retrieval computational prototype based on transcribed speech. Multimedia Tools and Applications, 80( 5), 33971-34017. doi:10.1007/s11042-021-11401-1
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      Spolaôr N, Lee HD, Takaki WSR, Ensina LA, Parmezan ARS, Oliva JT, Coy CSR, Wu FC. A video indexing and retrieval computational prototype based on transcribed speech [Internet]. Multimedia Tools and Applications. 2021 ; 80( 5): 33971-34017.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-021-11401-1
    • Vancouver

      Spolaôr N, Lee HD, Takaki WSR, Ensina LA, Parmezan ARS, Oliva JT, Coy CSR, Wu FC. A video indexing and retrieval computational prototype based on transcribed speech [Internet]. Multimedia Tools and Applications. 2021 ; 80( 5): 33971-34017.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-021-11401-1
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: RECONHECIMENTO DE IMAGEM, VÍDEO, MULTIMÍDIA INTERATIVA, REDES NEURAIS, APRENDIZADO COMPUTACIONAL

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      TROJAHN, Tiago Henrique e GOULARTE, Rudinei. Temporal video scene segmentation using deep-learning. Multimedia Tools and Applications, v. 80, n. 12, p. 17487-17513, 2021Tradução . . Disponível em: https://doi.org/10.1007/s11042-020-10450-2. Acesso em: 26 abr. 2024.
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      Trojahn, T. H., & Goularte, R. (2021). Temporal video scene segmentation using deep-learning. Multimedia Tools and Applications, 80( 12), 17487-17513. doi:10.1007/s11042-020-10450-2
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      Trojahn TH, Goularte R. Temporal video scene segmentation using deep-learning [Internet]. Multimedia Tools and Applications. 2021 ; 80( 12): 17487-17513.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-020-10450-2
    • Vancouver

      Trojahn TH, Goularte R. Temporal video scene segmentation using deep-learning [Internet]. Multimedia Tools and Applications. 2021 ; 80( 12): 17487-17513.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-020-10450-2
  • Source: Multimedia Tools and Applications. Unidade: EACH

    Subjects: FACE, RECONHECIMENTO DE PADRÕES, APRENDIZADO COMPUTACIONAL, FOTOGRAFIA

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      TESTA, Rafael Luiz e LIMA, Ariane Machado e MARQUES, Fátima de Lourdes dos Santos Nunes. Facial expression synthesis based on similar faces. Multimedia Tools and Applications, v. 80, p. Se 2021, 2021Tradução . . Disponível em: https://doi.org/10.1007/s11042-021-11525-4. Acesso em: 26 abr. 2024.
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      Testa, R. L., Lima, A. M., & Marques, F. de L. dos S. N. (2021). Facial expression synthesis based on similar faces. Multimedia Tools and Applications, 80, Se 2021. doi:10.1007/s11042-021-11525-4
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      Testa RL, Lima AM, Marques F de L dos SN. Facial expression synthesis based on similar faces [Internet]. Multimedia Tools and Applications. 2021 ; 80 Se 2021.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-021-11525-4
    • Vancouver

      Testa RL, Lima AM, Marques F de L dos SN. Facial expression synthesis based on similar faces [Internet]. Multimedia Tools and Applications. 2021 ; 80 Se 2021.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-021-11525-4
  • Source: Multimedia Tools and Applications. Unidades: ICMC, EESC

    Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, OLHO

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      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: 26 abr. 2024.
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      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
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      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 abr. 26 ] 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 abr. 26 ] Available from: https://doi.org/10.1007/s11042-020-10384-9
  • Source: Multimedia Tools and Applications. Unidades: EP, EACH

    Subjects: ALGORITMOS, COMPUTAÇÃO GRÁFICA

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      SANCHES, Silvio Ricardo Rodrigues et al. PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms. Multimedia Tools and Applications, v. no 2019, n. 22, p. 32393-32417, 2019Tradução . . Disponível em: https://doi.org/10.1007/s11042-019-07958-7. Acesso em: 26 abr. 2024.
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      Sanches, S. R. R., Sementille, A. C., Tori, R., Nakamura, R., & Silva, V. F. da. (2019). PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms. Multimedia Tools and Applications, no 2019( 22), 32393-32417. doi:10.1007/s11042-019-07958-7
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      Sanches SRR, Sementille AC, Tori R, Nakamura R, Silva VF da. PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms [Internet]. Multimedia Tools and Applications. 2019 ; no 2019( 22): 32393-32417.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-019-07958-7
    • Vancouver

      Sanches SRR, Sementille AC, Tori R, Nakamura R, Silva VF da. PAD: a perceptual application-dependent metric for quality assessment of segmentation algorithms [Internet]. Multimedia Tools and Applications. 2019 ; no 2019( 22): 32393-32417.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-019-07958-7
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: MULTIMÍDIA INTERATIVA, RECUPERAÇÃO DA INFORMAÇÃO, VÍDEO

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      KISHI, Rodrigo Mitsuo e TROJAHN, Tiago Henrique e GOULARTE, Rudinei. Correlation based feature fusion for the temporal video scene segmentation task. Multimedia Tools and Applications, v. 78, n. 11, p. 15623-15646, 2019Tradução . . Disponível em: https://doi.org/10.1007/s11042-018-6959-4. Acesso em: 26 abr. 2024.
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      Kishi, R. M., Trojahn, T. H., & Goularte, R. (2019). Correlation based feature fusion for the temporal video scene segmentation task. Multimedia Tools and Applications, 78( 11), 15623-15646. doi:10.1007/s11042-018-6959-4
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      Kishi RM, Trojahn TH, Goularte R. Correlation based feature fusion for the temporal video scene segmentation task [Internet]. Multimedia Tools and Applications. 2019 ; 78( 11): 15623-15646.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-018-6959-4
    • Vancouver

      Kishi RM, Trojahn TH, Goularte R. Correlation based feature fusion for the temporal video scene segmentation task [Internet]. Multimedia Tools and Applications. 2019 ; 78( 11): 15623-15646.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-018-6959-4
  • Source: Multimedia Tools and Applications. Unidade: EESC

    Subjects: ÍRIS, BIOMETRIA, PUPILA, ENGENHARIA ELÉTRICA

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      SOUZA, Jones Mendonça de e GONZAGA, Adilson. Human iris feature extraction under pupil size variation using local texture descriptors. Multimedia Tools and Applications, 2019Tradução . . Disponível em: https://doi.org/10.1007/s11042-019-7371-4. Acesso em: 26 abr. 2024.
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      Souza, J. M. de, & Gonzaga, A. (2019). Human iris feature extraction under pupil size variation using local texture descriptors. Multimedia Tools and Applications. doi:10.1007/s11042-019-7371-4
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      Souza JM de, Gonzaga A. Human iris feature extraction under pupil size variation using local texture descriptors [Internet]. Multimedia Tools and Applications. 2019 ;[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-019-7371-4
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      Souza JM de, Gonzaga A. Human iris feature extraction under pupil size variation using local texture descriptors [Internet]. Multimedia Tools and Applications. 2019 ;[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-019-7371-4
  • Source: Multimedia Tools and Applications. Unidade: EESC

    Subjects: RECONHECIMENTO DE IMAGEM, ENGENHARIA ELÉTRICA

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      VIEIRA, Raissa Tavares e NEGRI, Tamiris Trevisan e GONZAGA, Adilson. Improving the classification of rotated images by adding the signal and magnitude information to a local texture descriptor. Multimedia Tools and Applications, 2018Tradução . . Disponível em: https://doi.org/10.1007/s11042-018-6204-1. Acesso em: 26 abr. 2024.
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      Vieira, R. T., Negri, T. T., & Gonzaga, A. (2018). Improving the classification of rotated images by adding the signal and magnitude information to a local texture descriptor. Multimedia Tools and Applications. doi:10.1007/s11042-018-6204-1
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      Vieira RT, Negri TT, Gonzaga A. Improving the classification of rotated images by adding the signal and magnitude information to a local texture descriptor [Internet]. Multimedia Tools and Applications. 2018 ;[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-018-6204-1
    • Vancouver

      Vieira RT, Negri TT, Gonzaga A. Improving the classification of rotated images by adding the signal and magnitude information to a local texture descriptor [Internet]. Multimedia Tools and Applications. 2018 ;[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-018-6204-1
  • Source: Multimedia Tools and Applications. Unidade: EESC

    Subjects: PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE OBJETOS, RECONHECIMENTO DE PADRÕES, VISÃO COMPUTACIONAL

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      FERRAZ, Carolina Toledo e GONZAGA, Adilson. Object classification using a local texture descriptor and a support vector machine. Multimedia Tools and Applications, v. 76, p. 20609–20641, 2017Tradução . . Disponível em: http://dx.org.br/10.1007/s11042-016-4003-0. Acesso em: 26 abr. 2024.
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      Ferraz, C. T., & Gonzaga, A. (2017). Object classification using a local texture descriptor and a support vector machine. Multimedia Tools and Applications, 76, 20609–20641. doi:10.1007/s11042-016-4003-0
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      Ferraz CT, Gonzaga A. Object classification using a local texture descriptor and a support vector machine [Internet]. Multimedia Tools and Applications. 2017 ; 76 20609–20641.[citado 2024 abr. 26 ] Available from: http://dx.org.br/10.1007/s11042-016-4003-0
    • Vancouver

      Ferraz CT, Gonzaga A. Object classification using a local texture descriptor and a support vector machine [Internet]. Multimedia Tools and Applications. 2017 ; 76 20609–20641.[citado 2024 abr. 26 ] Available from: http://dx.org.br/10.1007/s11042-016-4003-0
  • Source: Multimedia Tools and Applications. Unidade: ICMC

    Subjects: BANCO DE DADOS, PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, COMPUTAÇÃO GRÁFICA

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      PEDROSA, Glauco V e TRAINA, Agma Juci Machado e BARCELOS, Celia A. Z. Retrieving 2D shapes by similarity based on bag of salience points. Multimedia Tools and Applications, v. 76, n. 20, p. 20957-20971, 2017Tradução . . Disponível em: https://doi.org/10.1007/s11042-016-4046-2. Acesso em: 26 abr. 2024.
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      Pedrosa, G. V., Traina, A. J. M., & Barcelos, C. A. Z. (2017). Retrieving 2D shapes by similarity based on bag of salience points. Multimedia Tools and Applications, 76( 20), 20957-20971. doi:10.1007/s11042-016-4046-2
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      Pedrosa GV, Traina AJM, Barcelos CAZ. Retrieving 2D shapes by similarity based on bag of salience points [Internet]. Multimedia Tools and Applications. 2017 ; 76( 20): 20957-20971.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-016-4046-2
    • Vancouver

      Pedrosa GV, Traina AJM, Barcelos CAZ. Retrieving 2D shapes by similarity based on bag of salience points [Internet]. Multimedia Tools and Applications. 2017 ; 76( 20): 20957-20971.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1007/s11042-016-4046-2

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