Proceedings of 21st National Meeting on Artificial and Computational Intelligence (2024)
- Authors:
- Autor USP: SILVA, DIEGO FURTADO - ICMC
- Unidade: ICMC
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Português
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2024
- Source:
- ISSN: 2763-9061
- Conference titles: Encontro Nacional de Inteligência Artificial e Computacional - ENIAC
-
ABNT
Proceedings of 21st National Meeting on Artificial and Computational Intelligence. . Porto Alegre: SBC. Disponível em: https://sol.sbc.org.br/index.php/eniac/. Acesso em: 10 fev. 2026. , 2024 -
APA
Proceedings of 21st National Meeting on Artificial and Computational Intelligence. (2024). Proceedings of 21st National Meeting on Artificial and Computational Intelligence. Porto Alegre: SBC. Recuperado de https://sol.sbc.org.br/index.php/eniac/ -
NLM
Proceedings of 21st National Meeting on Artificial and Computational Intelligence [Internet]. 2024 ;[citado 2026 fev. 10 ] Available from: https://sol.sbc.org.br/index.php/eniac/ -
Vancouver
Proceedings of 21st National Meeting on Artificial and Computational Intelligence [Internet]. 2024 ;[citado 2026 fev. 10 ] Available from: https://sol.sbc.org.br/index.php/eniac/ - Large scale similarity-based time series mining
- A divergence-based pruning approach for tree selection in continuous data streams
- Enhancing random forest for continuous data streams using divergence measures to select decision trees
- Classificação de séries temporais por similaridade e extração de atributos com aplicação na identificação automática de insetos
- Unsupervised feature based algorithms for time series extrinsic regression
- Noisy self-training with data augmentations for offensive and hate speech detection tasks
- Evaluating sentiment quantification methods in brazilian portuguese corpora
- Match: a maximum-likelihood approach for classification under label shift
- A new time series framework for forest fire risk forecasting and classification
- Large-scale similarity-based time series mining
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