Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling (2021)
- Authors:
- USP affiliated authors: PONTI, MOACIR ANTONELLI - ICMC ; SANTOS, FERNANDO PEREIRA DOS - ICMC
- Unidade: ICMC
- DOI: 10.1109/SIBGRAPI54419.2021.00036
- Subjects: REDES NEURAIS; RECONHECIMENTO DE IMAGEM; APRENDIZADO COMPUTACIONAL
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2021
- Source:
- Título: Proceedings
- Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SANTOS, Fernando Pereira dos e THUMÉ, Gabriela Salvador e PONTI, Moacir Antonelli. Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/SIBGRAPI54419.2021.00036. Acesso em: 13 fev. 2026. -
APA
Santos, F. P. dos, Thumé, G. S., & Ponti, M. A. (2021). Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling. In Proceedings. Los Alamitos: IEEE. doi:10.1109/SIBGRAPI54419.2021.00036 -
NLM
Santos FP dos, Thumé GS, Ponti MA. Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling [Internet]. Proceedings. 2021 ;[citado 2026 fev. 13 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00036 -
Vancouver
Santos FP dos, Thumé GS, Ponti MA. Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling [Internet]. Proceedings. 2021 ;[citado 2026 fev. 13 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00036 - Alignment of local and global features from multiple layers of convolutional neural network for image classification
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Informações sobre o DOI: 10.1109/SIBGRAPI54419.2021.00036 (Fonte: oaDOI API)
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