Compact descriptors for sketch-based image retrieval using a triplet loss convolutional neural network (2017)
- Authors:
- Autor USP: PONTI, MOACIR ANTONELLI - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.cviu.2017.06.007
- Subjects: PROCESSAMENTO DE IMAGENS; RECONHECIMENTO DE IMAGEM; APRENDIZADO COMPUTACIONAL; REDES NEURAIS
- Keywords: Sketch based image retrieval (SBIR); Deep learning; Triplet loss function; Cross-domain modelling; Compact feature representations
- Language: Inglês
- Imprenta:
- Source:
- Título: Computer Vision and Image Understanding
- ISSN: 1077-3142
- Volume/Número/Paginação/Ano: v. 164, p. 27-37, Nov. 2017
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
BUI, T et al. Compact descriptors for sketch-based image retrieval using a triplet loss convolutional neural network. Computer Vision and Image Understanding, v. No 2017, p. 27-37, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.cviu.2017.06.007. Acesso em: 04 ago. 2025. -
APA
Bui, T., Ribeiro, L., Ponti, M. A., & Collomosse, J. (2017). Compact descriptors for sketch-based image retrieval using a triplet loss convolutional neural network. Computer Vision and Image Understanding, No 2017, 27-37. doi:10.1016/j.cviu.2017.06.007 -
NLM
Bui T, Ribeiro L, Ponti MA, Collomosse J. Compact descriptors for sketch-based image retrieval using a triplet loss convolutional neural network [Internet]. Computer Vision and Image Understanding. 2017 ; No 2017 27-37.[citado 2025 ago. 04 ] Available from: https://doi.org/10.1016/j.cviu.2017.06.007 -
Vancouver
Bui T, Ribeiro L, Ponti MA, Collomosse J. Compact descriptors for sketch-based image retrieval using a triplet loss convolutional neural network [Internet]. Computer Vision and Image Understanding. 2017 ; No 2017 27-37.[citado 2025 ago. 04 ] Available from: https://doi.org/10.1016/j.cviu.2017.06.007 - One-class to multi-class model update using the class-incremental optimum-path forest classifier
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Informações sobre o DOI: 10.1016/j.cviu.2017.06.007 (Fonte: oaDOI API)
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