Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments

Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an...

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Detalles Bibliográficos
Autores principales: Han, Wenjing, Coutinho, Eduardo, Ruan, Huabin, Li, Haifeng, Schuller, Björn, Yu, Xiaojie, Zhu, Xuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5023122/
https://www.ncbi.nlm.nih.gov/pubmed/27627768
http://dx.doi.org/10.1371/journal.pone.0162075

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5023122/
https://www.ncbi.nlm.nih.gov/pubmed/27627768
http://dx.doi.org/10.1371/journal.pone.0162075

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