DeepMap+: Recognizing High-Level Indoor Semantics Using Virtual Features and Samples Based on a Multi-Length Window Framework

Existing indoor semantic recognition schemes are mostly capable of discovering patterns through smartphone sensing, but it is hard to recognize rich enough high-level indoor semantics for map enhancement. In this work we present DeepMap+, an automatical inference system for recognizing high-level in...

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Detalles Bibliográficos
Autores principales: Zhang, Wei, Zhou, Siwang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492840/
https://www.ncbi.nlm.nih.gov/pubmed/28587117
http://dx.doi.org/10.3390/s17061214

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492840/
https://www.ncbi.nlm.nih.gov/pubmed/28587117
http://dx.doi.org/10.3390/s17061214

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