Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis (2018)
- Authors:
- Autor USP: PONTI, MOACIR ANTONELLI - ICMC
- Unidade: ICMC
- DOI: 10.1109/SIBGRAPI.2018.00063
- Subjects: APRENDIZADO COMPUTACIONAL; PROCESSAMENTO DE IMAGENS
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2018
- Source:
- Título: Proceedings
- ISSN: 2377-5416
- Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
CAVALLARI, Gabriel B e RIBEIRO, Leonardo Sampaio F e PONTI, Moacir Antonelli. Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis. 2018, Anais.. Los Alamitos: IEEE, 2018. Disponível em: https://doi.org/10.1109/SIBGRAPI.2018.00063. Acesso em: 04 mar. 2026. -
APA
Cavallari, G. B., Ribeiro, L. S. F., & Ponti, M. A. (2018). Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis. In Proceedings. Los Alamitos: IEEE. doi:10.1109/SIBGRAPI.2018.00063 -
NLM
Cavallari GB, Ribeiro LSF, Ponti MA. Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis [Internet]. Proceedings. 2018 ;[citado 2026 mar. 04 ] Available from: https://doi.org/10.1109/SIBGRAPI.2018.00063 -
Vancouver
Cavallari GB, Ribeiro LSF, Ponti MA. Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis [Internet]. Proceedings. 2018 ;[citado 2026 mar. 04 ] Available from: https://doi.org/10.1109/SIBGRAPI.2018.00063 - Mobile inertial sensors for fall risk screening and prediction
- A decision cognizant Kullback-Leibler divergence
- Deep manifold alignment for mid-grain sketch based image retrieval
- Como funciona o deep learning
- Sketching out the details: sketch-based image retrieval using convolutional neural networks with multi-stage regression
- Generalization of feature embeddings transferred from different video anomaly detection domains
- An incremental linear-time learning algorithm for the optimum-path forest classifier
- Relevance image sampling from collection using importance selection on randomized optimum-path trees
- Compact descriptors for sketch-based image retrieval using a triplet loss convolutional neural network
- Better than counting seconds: identifying fallers among healthy elderly using fusion of accelerometer features and dual-task timed up and go
Informações sobre o DOI: 10.1109/SIBGRAPI.2018.00063 (Fonte: oaDOI API)
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
