Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections (2019)
- Authors:
- Autor USP: PONTI, MOACIR ANTONELLI - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.asoc.2019.04.013
- Subjects: APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE IMAGEM; ALGORITMOS PARA IMAGENS
- Keywords: Image classification; Relevance sampling; Feature learning; Clustering
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Applied Soft Computing
- ISSN: 1568-4946
- Volume/Número/Paginação/Ano: v. 80, p. 414-424, July 2019
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
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ABNT
PONTI, Moacir Antonelli et al. Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections. Applied Soft Computing, v. 80, p. 414-424, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2019.04.013. Acesso em: 10 out. 2024. -
APA
Ponti, M. A., Costa, G. B. P. da, Santos, F. P. dos, & Silveira, K. U. (2019). Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections. Applied Soft Computing, 80, 414-424. doi:10.1016/j.asoc.2019.04.013 -
NLM
Ponti MA, Costa GBP da, Santos FP dos, Silveira KU. Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections [Internet]. Applied Soft Computing. 2019 ; 80 414-424.[citado 2024 out. 10 ] Available from: https://doi.org/10.1016/j.asoc.2019.04.013 -
Vancouver
Ponti MA, Costa GBP da, Santos FP dos, Silveira KU. Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections [Internet]. Applied Soft Computing. 2019 ; 80 414-424.[citado 2024 out. 10 ] Available from: https://doi.org/10.1016/j.asoc.2019.04.013 - Better than counting seconds: identifying fallers among healthy elderly using fusion of accelerometer features and dual-task timed up and go
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Informações sobre o DOI: 10.1016/j.asoc.2019.04.013 (Fonte: oaDOI API)
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