Attributes’ Importance for Zero-Shot Pose-Classification Based on Wearable Sensors

This paper presents a simple yet effective method for improving the performance of zero-shot learning (ZSL). ZSL classifies instances of unseen classes, from which no training data is available, by utilizing the attributes of the classes. Conventional ZSL methods have equally dealt with all the avai...

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Detalles Bibliográficos
Autores principales: Ohashi, Hiroki, Al-Naser, Mohammad, Ahmed, Sheraz, Nakamura, Katsuyuki, Sato, Takuto, Dengel, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111934/
https://www.ncbi.nlm.nih.gov/pubmed/30071586
http://dx.doi.org/10.3390/s18082485

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111934/
https://www.ncbi.nlm.nih.gov/pubmed/30071586
http://dx.doi.org/10.3390/s18082485

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