Alignment of local and global features from multiple layers of convolutional neural network for image classification (2019)
- Authors:
- USP affiliated authors: PONTI, MOACIR ANTONELLI - ICMC ; SANTOS, FERNANDO PEREIRA DOS - ICMC
- Unidade: ICMC
- DOI: 10.1109/SIBGRAPI.2019.00040
- Subjects: REDES NEURAIS; RECONHECIMENTO DE IMAGEM
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2019
- Source:
- Título: Proceedings
- ISSN: 2377-5416
- Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SANTOS, Fernando Pereira dos e PONTI, Moacir Antonelli. Alignment of local and global features from multiple layers of convolutional neural network for image classification. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/SIBGRAPI.2019.00040. Acesso em: 28 dez. 2025. -
APA
Santos, F. P. dos, & Ponti, M. A. (2019). Alignment of local and global features from multiple layers of convolutional neural network for image classification. In Proceedings. Los Alamitos: IEEE. doi:10.1109/SIBGRAPI.2019.00040 -
NLM
Santos FP dos, Ponti MA. Alignment of local and global features from multiple layers of convolutional neural network for image classification [Internet]. Proceedings. 2019 ;[citado 2025 dez. 28 ] Available from: https://doi.org/10.1109/SIBGRAPI.2019.00040 -
Vancouver
Santos FP dos, Ponti MA. Alignment of local and global features from multiple layers of convolutional neural network for image classification [Internet]. Proceedings. 2019 ;[citado 2025 dez. 28 ] Available from: https://doi.org/10.1109/SIBGRAPI.2019.00040 - Data augmentation guidelines for cross-dataset transfer learning and pseudo labeling
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Informações sobre o DOI: 10.1109/SIBGRAPI.2019.00040 (Fonte: oaDOI API)
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