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Trabalho de evento
Convolutional neural networks enriched by handcrafted attributes (Enriched-CNN): an innovative approach to pattern recognition in histological images (2025)
Santos, Luiz Fernando Segato dos ; Neves, Leandro Alves ; Martins, Alessandro Santana ; Roberto, Guilherme Freire ; Tosta, Thaína Aparecida Azevedo ; Nascimento, Marcelo Zanchetta do
Source: Proceedings. Conference titles: International Conference on Enterprise Information Systems - ICEIS. Unidade: ICMC
Subjects: REDES NEURAIS, RECONHECIMENTO DE IMAGEM, FRACTAIS, HISTOLOGIA
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ABNT
SANTOS, Luiz Fernando Segato dos et al. Convolutional neural networks enriched by handcrafted attributes (Enriched-CNN): an innovative approach to pattern recognition in histological images. 2025, Anais.. Setúbal: SciTePress, 2025. Disponível em: https://doi.org/10.5220/0013277300003929. Acesso em: 05 dez. 2025.
APA
Santos, L. F. S. dos, Neves, L. A., Martins, A. S., Roberto, G. F., Tosta, T. A. A., & Nascimento, M. Z. do. (2025). Convolutional neural networks enriched by handcrafted attributes (Enriched-CNN): an innovative approach to pattern recognition in histological images. In Proceedings. Setúbal: SciTePress. doi:10.5220/0013277300003929
NLM
Santos LFS dos, Neves LA, Martins AS, Roberto GF, Tosta TAA, Nascimento MZ do. Convolutional neural networks enriched by handcrafted attributes (Enriched-CNN): an innovative approach to pattern recognition in histological images [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.5220/0013277300003929
Vancouver
Santos LFS dos, Neves LA, Martins AS, Roberto GF, Tosta TAA, Nascimento MZ do. Convolutional neural networks enriched by handcrafted attributes (Enriched-CNN): an innovative approach to pattern recognition in histological images [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.5220/0013277300003929
Trabalho de evento
Improving U-Net with attention mechanism for medical image segmentation applications (2025)
Honorato, Eduardo Sperle ; Uchida, Mariana Aya Suzuki ; Traina, Agma Juci Machado ; Wolf, Denis Fernando
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: VISÃO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, REDES NEURAIS, DIAGNÓSTICO POR IMAGEM
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ABNT
HONORATO, Eduardo Sperle et al. Improving U-Net with attention mechanism for medical image segmentation applications. 2025, Anais.. Los Alamitos: IEEE, 2025. Disponível em: https://doi.org/10.1109/CBMS65348.2025.00060. Acesso em: 05 dez. 2025.
APA
Honorato, E. S., Uchida, M. A. S., Traina, A. J. M., & Wolf, D. F. (2025). Improving U-Net with attention mechanism for medical image segmentation applications. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS65348.2025.00060
NLM
Honorato ES, Uchida MAS, Traina AJM, Wolf DF. Improving U-Net with attention mechanism for medical image segmentation applications [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00060
Vancouver
Honorato ES, Uchida MAS, Traina AJM, Wolf DF. Improving U-Net with attention mechanism for medical image segmentation applications [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00060
Artigo de periodico
Integrating machine learning and data augmentation for automated texture classification in borehole image logs (2025)
Souza, André Moreira ; Cruz, Matheus Altomare ; Braga, Paola M. C; Piva, Rodrigo B ; Dias, Rodrigo A. C ; Siqueira, Paulo R; Trevizan, Willian A; Jesus, Candida M. de; Bazzarella, Camilla ; Monteiro, Rodrigo Salvador ; Bernardini, Flávia Cristina ; Fernandes, Leandro Augusto Frata ; Sousa, Elaine Parros Machado de ; Cazzolato, Mirela Teixeira ; Oliveira, Daniel de ; Bedo, Marcos Vinicius Naves
Source: Proceedings. Conference titles: SPWLA Annual Logging Symposium. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, VISÃO COMPUTACIONAL, GEOLOGIA DO PETRÓLEO
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ABNT
SOUZA, André Moreira et al. Integrating machine learning and data augmentation for automated texture classification in borehole image logs. Proceedings, 2025Tradução . . Disponível em: https://doi.org/10.30632/SPWLA-2025-0109. Acesso em: 05 dez. 2025.
APA
Souza, A. M., Cruz, M. A., Braga, P. M. C., Piva, R. B., Dias, R. A. C., Siqueira, P. R., et al. (2025). Integrating machine learning and data augmentation for automated texture classification in borehole image logs. Proceedings. doi:10.30632/SPWLA-2025-0109
NLM
Souza AM, Cruz MA, Braga PMC, Piva RB, Dias RAC, Siqueira PR, Trevizan WA, Jesus CM de, Bazzarella C, Monteiro RS, Bernardini FC, Fernandes LAF, Sousa EPM de, Cazzolato MT, Oliveira D de, Bedo MVN. Integrating machine learning and data augmentation for automated texture classification in borehole image logs [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.30632/SPWLA-2025-0109
Vancouver
Souza AM, Cruz MA, Braga PMC, Piva RB, Dias RAC, Siqueira PR, Trevizan WA, Jesus CM de, Bazzarella C, Monteiro RS, Bernardini FC, Fernandes LAF, Sousa EPM de, Cazzolato MT, Oliveira D de, Bedo MVN. Integrating machine learning and data augmentation for automated texture classification in borehole image logs [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.30632/SPWLA-2025-0109
Trabalho de evento
Density-guided rank correlation graphs for graph convolutional networks in image classification (2025)
Brito, Gabriel Maia; Valem, Lucas Pascotti
Source: Proceedings. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidades: ICMC, IFSC
Subjects: REDES NEURAIS, RECONHECIMENTO DE IMAGEM, TEORIA DOS GRAFOS
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ABNT
BRITO, Gabriel Maia e VALEM, Lucas Pascotti. Density-guided rank correlation graphs for graph convolutional networks in image classification. 2025, Anais.. Piscataway: IEEE, 2025. Disponível em: https://doi.org/10.1109/SIBGRAPI67909.2025.11223391. Acesso em: 05 dez. 2025.
APA
Brito, G. M., & Valem, L. P. (2025). Density-guided rank correlation graphs for graph convolutional networks in image classification. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI67909.2025.11223391
NLM
Brito GM, Valem LP. Density-guided rank correlation graphs for graph convolutional networks in image classification [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/SIBGRAPI67909.2025.11223391
Vancouver
Brito GM, Valem LP. Density-guided rank correlation graphs for graph convolutional networks in image classification [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/SIBGRAPI67909.2025.11223391
Trabalho de evento
Association of fractal geometry and data augmentation through GANs and XAI for classification of histology images (2025)
Borgue, Vinicius Augusto Toreli ; Garcia, Bianca Lançoni de Oliveira ; Pelicano Junior, Sérgio Augusto ; Roberto, Guilherme Freire ; Rozendo, Guilherme Botazzo ; Neves, Leandro Alves ; Martins, Alessandro Santana ; Tosta, Thaína Aparecida Azevedo ; Nascimento, Marcelo Zanchetta do
Source: Proceedings. Conference titles: International Conference on Enterprise Information Systems - ICEIS. Unidade: ICMC
Subjects: REDES NEURAIS, RECONHECIMENTO DE IMAGEM, FRACTAIS, HISTOLOGIA
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ABNT
BORGUE, Vinicius Augusto Toreli et al. Association of fractal geometry and data augmentation through GANs and XAI for classification of histology images. 2025, Anais.. Setúbal: SciTePress, 2025. Disponível em: https://doi.org/10.5220/0013280200003929. Acesso em: 05 dez. 2025.
APA
Borgue, V. A. T., Garcia, B. L. de O., Pelicano Junior, S. A., Roberto, G. F., Rozendo, G. B., Neves, L. A., et al. (2025). Association of fractal geometry and data augmentation through GANs and XAI for classification of histology images. In Proceedings. Setúbal: SciTePress. doi:10.5220/0013280200003929
NLM
Borgue VAT, Garcia BL de O, Pelicano Junior SA, Roberto GF, Rozendo GB, Neves LA, Martins AS, Tosta TAA, Nascimento MZ do. Association of fractal geometry and data augmentation through GANs and XAI for classification of histology images [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.5220/0013280200003929
Vancouver
Borgue VAT, Garcia BL de O, Pelicano Junior SA, Roberto GF, Rozendo GB, Neves LA, Martins AS, Tosta TAA, Nascimento MZ do. Association of fractal geometry and data augmentation through GANs and XAI for classification of histology images [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.5220/0013280200003929
Trabalho de evento
Neural network-based velocity control for dynamic obstacle avoidance in legged robots (2025)
Garcia, João Pedro Baltieca; Negri, Juliano Decico; Medeiros, Vivian Suzano; Becker, Marcelo
Source: Proceedings. Conference titles: Brazilian Conference on Robotics - CROS. Unidade: EESC
Subjects: ENGENHARIA MECÂNICA, VELOCIDADE, REDES NEURAIS, ROBÔS, ROBÓTICA
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ABNT
GARCIA, João Pedro Baltieca et al. Neural network-based velocity control for dynamic obstacle avoidance in legged robots. 2025, Anais.. Piscataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2025. Disponível em: http://dx.doi.org/10.1109/CROS66186.2025.11064871. Acesso em: 05 dez. 2025.
APA
Garcia, J. P. B., Negri, J. D., Medeiros, V. S., & Becker, M. (2025). Neural network-based velocity control for dynamic obstacle avoidance in legged robots. In Proceedings. Piscataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1109/CROS66186.2025.11064871
NLM
Garcia JPB, Negri JD, Medeiros VS, Becker M. Neural network-based velocity control for dynamic obstacle avoidance in legged robots [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: http://dx.doi.org/10.1109/CROS66186.2025.11064871
Vancouver
Garcia JPB, Negri JD, Medeiros VS, Becker M. Neural network-based velocity control for dynamic obstacle avoidance in legged robots [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: http://dx.doi.org/10.1109/CROS66186.2025.11064871
Trabalho de evento
State estimation of autonomous terrestrial robot using a neural network model (2025)
Ugucioni Filho, Fernando; Becker, Marcelo ; Higuti, Vitor Akihiro Hisano
Source: Proceedings. Conference titles: Brazilian Conference on Robotics - CROS. Unidade: EESC
Subjects: ENGENHARIA MECÂNICA, REDES NEURAIS, ROBÓTICA, ROBÔS
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ABNT
UGUCIONI FILHO, Fernando e BECKER, Marcelo e HIGUTI, Vitor Akihiro Hisano. State estimation of autonomous terrestrial robot using a neural network model. 2025, Anais.. Piscataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2025. Disponível em: http://dx.doi.org/10.1109/CROS66186.2025.11066128. Acesso em: 05 dez. 2025.
APA
Ugucioni Filho, F., Becker, M., & Higuti, V. A. H. (2025). State estimation of autonomous terrestrial robot using a neural network model. In Proceedings. Piscataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1109/CROS66186.2025.11066128
NLM
Ugucioni Filho F, Becker M, Higuti VAH. State estimation of autonomous terrestrial robot using a neural network model [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: http://dx.doi.org/10.1109/CROS66186.2025.11066128
Vancouver
Ugucioni Filho F, Becker M, Higuti VAH. State estimation of autonomous terrestrial robot using a neural network model [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: http://dx.doi.org/10.1109/CROS66186.2025.11066128
Trabalho de evento
Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences (2025)
Alam, Md Mahbub ; Soares, Amilcar ; Rodrigues Junior, José Fernando ; Spadon, Gabriel
Source: Proceedings. Conference titles: International Symposium on Spatial and Temporal Data - SSTD. Unidade: ICMC
Subjects: REDES NEURAIS, NAVEGAÇÃO MARÍTIMA
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ABNT
ALAM, Md Mahbub et al. Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences. 2025, Anais.. New York: ACM, 2025. Disponível em: https://doi.org/10.1145/3748777.3748779. Acesso em: 05 dez. 2025.
APA
Alam, M. M., Soares, A., Rodrigues Junior, J. F., & Spadon, G. (2025). Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences. In Proceedings. New York: ACM. doi:10.1145/3748777.3748779
NLM
Alam MM, Soares A, Rodrigues Junior JF, Spadon G. Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1145/3748777.3748779
Vancouver
Alam MM, Soares A, Rodrigues Junior JF, Spadon G. Physics-informed neural networks for vessel trajectory prediction: learning time-discretized kinematic dynamics via finite differences [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1145/3748777.3748779
Trabalho de evento
Rank-based unsupervised similarity learning: framework and applications (2025)
Saldanha, Italo de Matos; Kawai, Vinicius Atsushi Sato; Rozin, Bionda ; Leticio, Gustavo Rosseto ; Valem, Lucas Pascotti ; Pedronette, Daniel Carlos Guimarães
Source: Proceedings. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: ICMC
Subjects: REDES NEURAIS, TEORIA DOS GRAFOS, RECONHECIMENTO DE IMAGEM
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ABNT
SALDANHA, Italo de Matos et al. Rank-based unsupervised similarity learning: framework and applications. 2025, Anais.. Piscataway: IEEE, 2025. Disponível em: https://doi.org/10.1109/SIBGRAPI67909.2025.11223278. Acesso em: 05 dez. 2025.
APA
Saldanha, I. de M., Kawai, V. A. S., Rozin, B., Leticio, G. R., Valem, L. P., & Pedronette, D. C. G. (2025). Rank-based unsupervised similarity learning: framework and applications. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI67909.2025.11223278
NLM
Saldanha I de M, Kawai VAS, Rozin B, Leticio GR, Valem LP, Pedronette DCG. Rank-based unsupervised similarity learning: framework and applications [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/SIBGRAPI67909.2025.11223278
Vancouver
Saldanha I de M, Kawai VAS, Rozin B, Leticio GR, Valem LP, Pedronette DCG. Rank-based unsupervised similarity learning: framework and applications [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/SIBGRAPI67909.2025.11223278
Trabalho de evento
Graph convolutional networks based on aggregated multilevel kNN graph for image classification (2025)
Leticio, Gustavo Rosseto ; Kawai, Vinicius Atsushi Sato; Valem, Lucas Pascotti ; Pedronette, Daniel Carlos Guimarães
Source: Proceedings. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: ICMC
Subjects: REDES NEURAIS, RECONHECIMENTO DE IMAGEM, TEORIA DOS GRAFOS
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ABNT
LETICIO, Gustavo Rosseto et al. Graph convolutional networks based on aggregated multilevel kNN graph for image classification. 2025, Anais.. Piscataway: IEEE, 2025. Disponível em: https://doi.org/10.1109/SIBGRAPI67909.2025.11223400. Acesso em: 05 dez. 2025.
APA
Leticio, G. R., Kawai, V. A. S., Valem, L. P., & Pedronette, D. C. G. (2025). Graph convolutional networks based on aggregated multilevel kNN graph for image classification. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI67909.2025.11223400
NLM
Leticio GR, Kawai VAS, Valem LP, Pedronette DCG. Graph convolutional networks based on aggregated multilevel kNN graph for image classification [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/SIBGRAPI67909.2025.11223400
Vancouver
Leticio GR, Kawai VAS, Valem LP, Pedronette DCG. Graph convolutional networks based on aggregated multilevel kNN graph for image classification [Internet]. Proceedings. 2025 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/SIBGRAPI67909.2025.11223400
Trabalho de evento
Exploring neighborhood variancy for rule search optimization in life-like network automata (2024)
Zielinski, Kallil Miguel Caparroz ; Scabini, Leonardo Felipe dos Santos ; Ribas, Lucas Correia ; Bruno, Odemir Martinez
Source: Proceedings. Conference titles: International Conference on Pattern Recognition Systems - ICPRS. Unidade: IFSC
Subjects: FÍSICA COMPUTACIONAL, APRENDIZADO COMPUTACIONAL, REDES NEURAIS, RECONHECIMENTO DE PADRÕES
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ABNT
ZIELINSKI, Kallil Miguel Caparroz et al. Exploring neighborhood variancy for rule search optimization in life-like network automata. 2024, Anais.. Piscataway: Institute of Electrical and Electronic Engineers - IEEE, 2024. Disponível em: https://doi.org/10.1109/ICPRS62101.2024.10677825. Acesso em: 05 dez. 2025.
APA
Zielinski, K. M. C., Scabini, L. F. dos S., Ribas, L. C., & Bruno, O. M. (2024). Exploring neighborhood variancy for rule search optimization in life-like network automata. In Proceedings. Piscataway: Institute of Electrical and Electronic Engineers - IEEE. doi:10.1109/ICPRS62101.2024.10677825
NLM
Zielinski KMC, Scabini LF dos S, Ribas LC, Bruno OM. Exploring neighborhood variancy for rule search optimization in life-like network automata [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/ICPRS62101.2024.10677825
Vancouver
Zielinski KMC, Scabini LF dos S, Ribas LC, Bruno OM. Exploring neighborhood variancy for rule search optimization in life-like network automata [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/ICPRS62101.2024.10677825
Trabalho de evento
Real-time intrusion detection with sequence-aware neural networks for Internet of medical things (2024)
Werneck, Heitor; Batista, Daniel Macêdo ; Hirata Júnior, Roberto ; Queiroz, Marcelo Gomes de
Source: Proceedings. Conference titles: Virtual Conference on Communications - VCC. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, INTERNET DAS COISAS, SAÚDE, REDES NEURAIS, GESTÃO DA SEGURANÇA EM SISTEMAS COMPUTACIONAIS
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ABNT
WERNECK, Heitor et al. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/VCC63113.2024.10914399. Acesso em: 05 dez. 2025.
APA
Werneck, H., Batista, D. M., Hirata Júnior, R., & Queiroz, M. G. de. (2024). Real-time intrusion detection with sequence-aware neural networks for Internet of medical things. In Proceedings. Piscataway: IEEE. doi:10.1109/VCC63113.2024.10914399
NLM
Werneck H, Batista DM, Hirata Júnior R, Queiroz MG de. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/VCC63113.2024.10914399
Vancouver
Werneck H, Batista DM, Hirata Júnior R, Queiroz MG de. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/VCC63113.2024.10914399
Trabalho de evento-anais periodico
An algorithm to train unrestricted sequential discrete morphological neural networks (2024)
Marcondes, Diego ; Feldman, Mariana de Sousa ; Barrera, Junior
Source: Proceedings. Conference titles: International Conference on Discrete Geometry and Mathematical Morphology - DGMM. Unidade: IME
Subjects: PROCESSAMENTO DE IMAGENS, REDES NEURAIS
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ABNT
MARCONDES, Diego e FELDMAN, Mariana de Sousa e BARRERA, Junior. An algorithm to train unrestricted sequential discrete morphological neural networks. Proceedings. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-57793-2_14. Acesso em: 05 dez. 2025. , 2024
APA
Marcondes, D., Feldman, M. de S., & Barrera, J. (2024). An algorithm to train unrestricted sequential discrete morphological neural networks. Proceedings. Cham: Springer. doi:10.1007/978-3-031-57793-2_14
NLM
Marcondes D, Feldman M de S, Barrera J. An algorithm to train unrestricted sequential discrete morphological neural networks [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1007/978-3-031-57793-2_14
Vancouver
Marcondes D, Feldman M de S, Barrera J. An algorithm to train unrestricted sequential discrete morphological neural networks [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1007/978-3-031-57793-2_14
Trabalho de evento
Enhancing safety via deep reinforcement learning in trajectory planning for agile flights in unknown environments (2024)
Rocha, Lidia; Bidinotto, Jorge Henrique ; Heintz, Frederik; Tiger, Mattias; Vivaldini, Kelen Cristiane Teixeira
Source: Proceedings. Conference titles: IEEE/RSJ International Conference on Intelligent Robots and Systems - IROS. Unidade: EESC
Subjects: TRAJETÓRIA, APRENDIZAGEM PROFUNDA, VOO (ENGENHARIA AERONÁUTICA), REDES NEURAIS, ENGENHARIA AERONÁUTICA
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ABNT
ROCHA, Lidia et al. Enhancing safety via deep reinforcement learning in trajectory planning for agile flights in unknown environments. 2024, Anais.. Piscataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2024. Disponível em: https://dx.doi.org/10.1109/IROS58592.2024.10801910. Acesso em: 05 dez. 2025.
APA
Rocha, L., Bidinotto, J. H., Heintz, F., Tiger, M., & Vivaldini, K. C. T. (2024). Enhancing safety via deep reinforcement learning in trajectory planning for agile flights in unknown environments. In Proceedings. Piscataway, NJ, USA: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1109/IROS58592.2024.10801910
NLM
Rocha L, Bidinotto JH, Heintz F, Tiger M, Vivaldini KCT. Enhancing safety via deep reinforcement learning in trajectory planning for agile flights in unknown environments [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://dx.doi.org/10.1109/IROS58592.2024.10801910
Vancouver
Rocha L, Bidinotto JH, Heintz F, Tiger M, Vivaldini KCT. Enhancing safety via deep reinforcement learning in trajectory planning for agile flights in unknown environments [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://dx.doi.org/10.1109/IROS58592.2024.10801910
Trabalho de evento
Machine learning techniques for improving multiclass anomaly detection on conveyor belts (2024)
Matos, Saulo Neves ; Coletti, Otavio Ferracioli ; Zimmer, Rafael; Ugucioni Filho, Fernando; Carvalho, Ricardo C. C. L. de; Silva, Victor Rodrigues da; Franco, Jorge Luiz; Pinto, Thomas Vargas Barsante e ; Barros, Luiz Guilherme Dias de ; Ranieri, Caetano Mazzoni ; Lopes, Bruno Eduardo; Silva, Diego Furtado ; Ueyama, Jó ; Pessin, Gustavo
Source: Proceedings. Conference titles: IEEE International Instrumentation and Measurement Technology Conference - I2MTC. Unidades: ICMC, EESC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, MANUTENÇÃO PREDITIVA, TRANSPORTADORES DE CORREIA
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ABNT
MATOS, Saulo Neves et al. Machine learning techniques for improving multiclass anomaly detection on conveyor belts. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/I2MTC60896.2024.10561167. Acesso em: 05 dez. 2025.
APA
Matos, S. N., Coletti, O. F., Zimmer, R., Ugucioni Filho, F., Carvalho, R. C. C. L. de, Silva, V. R. da, et al. (2024). Machine learning techniques for improving multiclass anomaly detection on conveyor belts. In Proceedings. Piscataway: IEEE. doi:10.1109/I2MTC60896.2024.10561167
NLM
Matos SN, Coletti OF, Zimmer R, Ugucioni Filho F, Carvalho RCCL de, Silva VR da, Franco JL, Pinto TVB e, Barros LGD de, Ranieri CM, Lopes BE, Silva DF, Ueyama J, Pessin G. Machine learning techniques for improving multiclass anomaly detection on conveyor belts [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/I2MTC60896.2024.10561167
Vancouver
Matos SN, Coletti OF, Zimmer R, Ugucioni Filho F, Carvalho RCCL de, Silva VR da, Franco JL, Pinto TVB e, Barros LGD de, Ranieri CM, Lopes BE, Silva DF, Ueyama J, Pessin G. Machine learning techniques for improving multiclass anomaly detection on conveyor belts [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/I2MTC60896.2024.10561167
Trabalho de evento
Randomized encoding ensemble: a new approach for texture representation (2024)
Fares, Ricardo Trivizan ; Vicentim, Ana Catarina Marques ; Scabini, Leonardo Felipe dos Santos ; Zielinski, Kallil Miguel Caparroz ; Jennane, Rachid ; Bruno, Odemir Martinez ; Ribas, Lucas Correia
Source: Proceedings. Conference titles: International Conference on Systems, Signals and Image Processing - IWSSIP. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, RECONHECIMENTO DE IMAGEM, PLANTAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FARES, Ricardo Trivizan et al. Randomized encoding ensemble: a new approach for texture representation. 2024, Anais.. Piscataway: Institute of Electrical and Electronic Engineers - IEEE, 2024. Disponível em: https://doi.org/10.1109/IWSSIP62407.2024.10634030. Acesso em: 05 dez. 2025.
APA
Fares, R. T., Vicentim, A. C. M., Scabini, L. F. dos S., Zielinski, K. M. C., Jennane, R., Bruno, O. M., & Ribas, L. C. (2024). Randomized encoding ensemble: a new approach for texture representation. In Proceedings. Piscataway: Institute of Electrical and Electronic Engineers - IEEE. doi:10.1109/IWSSIP62407.2024.10634030
NLM
Fares RT, Vicentim ACM, Scabini LF dos S, Zielinski KMC, Jennane R, Bruno OM, Ribas LC. Randomized encoding ensemble: a new approach for texture representation [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/IWSSIP62407.2024.10634030
Vancouver
Fares RT, Vicentim ACM, Scabini LF dos S, Zielinski KMC, Jennane R, Bruno OM, Ribas LC. Randomized encoding ensemble: a new approach for texture representation [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/IWSSIP62407.2024.10634030
Trabalho de evento
dPASP: a probabilistic logic programming environment for neurosymbolic learning and reasoning (2024)
Geh, Renato Lui ; Gonçalves, Jonas; Silveira, Igor Cataneo ; Mauá, Denis Deratani ; Cozman, Fabio Gagliardi
Source: Proceedings. Conference titles: International Conference on Principles of Knowledge Representation and Reasoning – KR. Unidades: IME, EP
Subjects: INTELIGÊNCIA ARTIFICIAL, PROGRAMAÇÃO LÓGICA, SEMÂNTICA, APRENDIZADO COMPUTACIONAL, COMPUTAÇÃO EVOLUTIVA, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GEH, Renato Lui et al. dPASP: a probabilistic logic programming environment for neurosymbolic learning and reasoning. 2024, Anais.. California: IJCAI Organization, 2024. Disponível em: https://doi.org/10.24963/kr.2024/69. Acesso em: 05 dez. 2025.
APA
Geh, R. L., Gonçalves, J., Silveira, I. C., Mauá, D. D., & Cozman, F. G. (2024). dPASP: a probabilistic logic programming environment for neurosymbolic learning and reasoning. In Proceedings. California: IJCAI Organization. doi:10.24963/kr.2024/69
NLM
Geh RL, Gonçalves J, Silveira IC, Mauá DD, Cozman FG. dPASP: a probabilistic logic programming environment for neurosymbolic learning and reasoning [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.24963/kr.2024/69
Vancouver
Geh RL, Gonçalves J, Silveira IC, Mauá DD, Cozman FG. dPASP: a probabilistic logic programming environment for neurosymbolic learning and reasoning [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.24963/kr.2024/69
Trabalho de evento
Modelling graph neural network by aggregating the activation maps of self-organizing map (2024)
Martins, Luan Vinicius de Carvalho ; Donghong, Ji; Liang, Zhao
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC
Subjects: REDES NEURAIS, TEORIA DOS GRAFOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINS, Luan Vinicius de Carvalho e DONGHONG, Ji e LIANG, Zhao. Modelling graph neural network by aggregating the activation maps of self-organizing map. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/IJCNN60899.2024.10650514. Acesso em: 05 dez. 2025.
APA
Martins, L. V. de C., Donghong, J., & Liang, Z. (2024). Modelling graph neural network by aggregating the activation maps of self-organizing map. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN60899.2024.10650514
NLM
Martins LV de C, Donghong J, Liang Z. Modelling graph neural network by aggregating the activation maps of self-organizing map [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650514
Vancouver
Martins LV de C, Donghong J, Liang Z. Modelling graph neural network by aggregating the activation maps of self-organizing map [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/IJCNN60899.2024.10650514
Trabalho de evento
Efficient parameter mining and freezing for continual object detection (2024)
Menezes, Angelo Garangau ; Peterlevitz, Augusto José ; Chinelatto, Mateus Antonio ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Source: Proceedings. Conference titles: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISIGRAPP. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, VISÃO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MENEZES, Angelo Garangau et al. Efficient parameter mining and freezing for continual object detection. 2024, Anais.. Setúbal: SciTePress, 2024. Disponível em: https://doi.org/10.5220/0012362300003660. Acesso em: 05 dez. 2025.
APA
Menezes, A. G., Peterlevitz, A. J., Chinelatto, M. A., & Carvalho, A. C. P. de L. F. de. (2024). Efficient parameter mining and freezing for continual object detection. In Proceedings. Setúbal: SciTePress. doi:10.5220/0012362300003660
NLM
Menezes AG, Peterlevitz AJ, Chinelatto MA, Carvalho ACP de LF de. Efficient parameter mining and freezing for continual object detection [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.5220/0012362300003660
Vancouver
Menezes AG, Peterlevitz AJ, Chinelatto MA, Carvalho ACP de LF de. Efficient parameter mining and freezing for continual object detection [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.5220/0012362300003660
Trabalho de evento
Sensor fusion of LiDAR and stereo camera for forest mapping (2024)
Souza Neto, Amador Marcelino de; Romero, Roseli Aparecida Francelin
Source: Proceedings. Conference titles: Latin American Robotics Symposium - LARS. Unidade: ICMC
Subjects: VISÃO COMPUTACIONAL, REDES NEURAIS, PROCESSAMENTO DE IMAGENS, MONITORAMENTO AMBIENTAL, FLORESTAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA NETO, Amador Marcelino de e ROMERO, Roseli Aparecida Francelin. Sensor fusion of LiDAR and stereo camera for forest mapping. 2024, Anais.. Danvers: IEEE, 2024. Disponível em: https://doi.org/10.1109/LARS64411.2024.10786470. Acesso em: 05 dez. 2025.
APA
Souza Neto, A. M. de, & Romero, R. A. F. (2024). Sensor fusion of LiDAR and stereo camera for forest mapping. In Proceedings. Danvers: IEEE. doi:10.1109/LARS64411.2024.10786470
NLM
Souza Neto AM de, Romero RAF. Sensor fusion of LiDAR and stereo camera for forest mapping [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/LARS64411.2024.10786470
Vancouver
Souza Neto AM de, Romero RAF. Sensor fusion of LiDAR and stereo camera for forest mapping [Internet]. Proceedings. 2024 ;[citado 2025 dez. 05 ] Available from: https://doi.org/10.1109/LARS64411.2024.10786470

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