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Trabalho de evento
ARWithDistance: distance awareness in off-screen visualization techniques for AR applications (2023)
Afonso, Ana Paula; Carmo, Maria Beatriz ; Costa, Pedro; Pereira, Tiago
Source: Proceedings. Conference titles: International Conference Information Visualisation - IV. Unidade: ICMC
Subjects: REALIDADE AUMENTADA, ESTUDO DE USUÁRIOS, APLICATIVOS MÓVEIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AFONSO, Ana Paula et al. ARWithDistance: distance awareness in off-screen visualization techniques for AR applications. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IV60283.2023.00064. Acesso em: 17 nov. 2024.
APA
Afonso, A. P., Carmo, M. B., Costa, P., & Pereira, T. (2023). ARWithDistance: distance awareness in off-screen visualization techniques for AR applications. In Proceedings. Piscataway: IEEE. doi:10.1109/IV60283.2023.00064
NLM
Afonso AP, Carmo MB, Costa P, Pereira T. ARWithDistance: distance awareness in off-screen visualization techniques for AR applications [Internet]. Proceedings. 2023 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1109/IV60283.2023.00064
Vancouver
Afonso AP, Carmo MB, Costa P, Pereira T. ARWithDistance: distance awareness in off-screen visualization techniques for AR applications [Internet]. Proceedings. 2023 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1109/IV60283.2023.00064
Trabalho de evento
Late-fusion multimodal human detection based on RGB and thermal images for robotic perception (2023)
Sousa, Elísio ; Mota, Kennedy O. S ; Gomes, Iago Pachêco ; Garrote, Luís ; Wolf, Denis Fernando ; Premebida, Cristiano
Source: Proceedings. Conference titles: European Conference on Mobile Robots - ECMR. Unidade: ICMC
Subjects: RECONHECIMENTO DE IMAGEM, VEÍCULOS AUTÔNOMOS, APRENDIZAGEM PROFUNDA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUSA, Elísio et al. Late-fusion multimodal human detection based on RGB and thermal images for robotic perception. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/ECMR59166.2023.10256301. Acesso em: 17 nov. 2024.
APA
Sousa, E., Mota, K. O. S., Gomes, I. P., Garrote, L., Wolf, D. F., & Premebida, C. (2023). Late-fusion multimodal human detection based on RGB and thermal images for robotic perception. In Proceedings. Piscataway: IEEE. doi:10.1109/ECMR59166.2023.10256301
NLM
Sousa E, Mota KOS, Gomes IP, Garrote L, Wolf DF, Premebida C. Late-fusion multimodal human detection based on RGB and thermal images for robotic perception [Internet]. Proceedings. 2023 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1109/ECMR59166.2023.10256301
Vancouver
Sousa E, Mota KOS, Gomes IP, Garrote L, Wolf DF, Premebida C. Late-fusion multimodal human detection based on RGB and thermal images for robotic perception [Internet]. Proceedings. 2023 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1109/ECMR59166.2023.10256301
Trabalho de evento
Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools (2023)
Cazzolato, Mirela Teixeira ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Faloutsos, Christos ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: BANCO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO, VISUALIZAÇÃO, REGISTROS HOSPITALARES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00202. Acesso em: 17 nov. 2024.
APA
Cazzolato, M. T., Gutierrez, M. A., Traina Junior, C., Faloutsos, C., & Traina, A. J. M. (2023). Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS58004.2023.00202
NLM
Cazzolato MT, Gutierrez MA, Traina Junior C, Faloutsos C, Traina AJM. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools [Internet]. Proceedings. 2023 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00202
Vancouver
Cazzolato MT, Gutierrez MA, Traina Junior C, Faloutsos C, Traina AJM. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools [Internet]. Proceedings. 2023 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00202
Trabalho de evento
TgraphSpot: fast and effective anomaly detection for time-evolving graphs (2022)
Cazzolato, Mirela Teixeira ; Vijayakumar, Saranya; Zheng, Xinyi; Park, Namyong; Lee, Meng-Chieh; Fidalgo, Pedro; Lages, Bruno; Traina, Agma Juci Machado ; Faloutsos, Christos
Source: Proceedings. Conference titles: IEEE International Conference on Big Data - Big Data. Unidade: ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, VISUALIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. TgraphSpot: fast and effective anomaly detection for time-evolving graphs. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/BigData55660.2022.10020898. Acesso em: 17 nov. 2024.
APA
Cazzolato, M. T., Vijayakumar, S., Zheng, X., Park, N., Lee, M. -C., Fidalgo, P., et al. (2022). TgraphSpot: fast and effective anomaly detection for time-evolving graphs. In Proceedings. Piscataway: IEEE. doi:10.1109/BigData55660.2022.10020898
NLM
Cazzolato MT, Vijayakumar S, Zheng X, Park N, Lee M-C, Fidalgo P, Lages B, Traina AJM, Faloutsos C. TgraphSpot: fast and effective anomaly detection for time-evolving graphs [Internet]. Proceedings. 2022 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1109/BigData55660.2022.10020898
Vancouver
Cazzolato MT, Vijayakumar S, Zheng X, Park N, Lee M-C, Fidalgo P, Lages B, Traina AJM, Faloutsos C. TgraphSpot: fast and effective anomaly detection for time-evolving graphs [Internet]. Proceedings. 2022 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1109/BigData55660.2022.10020898

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