Hardness Recognition of Robotic Forearm Based on Semi-supervised Generative Adversarial Networks

The hardness recognition is of great significance to tactile sensing and robotic control. The hardness recognition methods based on deep learning have demonstrated a good performance, however, a huge amount of manually labeled samples which require lots of time and labor costs are necessary for the...

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Detalles Bibliográficos
Autores principales: Qian, Xiaoliang, Li, Erkai, Zhang, Jianwei, Zhao, Su-Na, Wu, Qing-E, Zhang, Huanlong, Wang, Wei, Wu, Yuanyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743412/
https://www.ncbi.nlm.nih.gov/pubmed/31551748
http://dx.doi.org/10.3389/fnbot.2019.00073

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743412/
https://www.ncbi.nlm.nih.gov/pubmed/31551748
http://dx.doi.org/10.3389/fnbot.2019.00073

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