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Home » A Deep Learning Approach for Indoor User Localization in Smart Environments

A Deep Learning Approach for Indoor User Localization in Smart Environments

TitleA Deep Learning Approach for Indoor User Localization in Smart Environments
Publication TypeConference Paper
Year of Publication2018
AuthorsDe Vita, F.., and D.. Bruneo
Conference Name2018 IEEE International Conference on Smart Computing (SMARTCOMP)
Date PublishedJune
KeywordsBuildings, cloud computing, Deep Learning, deep learning approach, Global Positioning System, Indoor environments, indoor localization, indoor navigation, indoor user localization, indoor user location, integral part, learning (artificial intelligence), Machine learning, radionavigation, smart environments, smart services, telecommunication computing, TensorFlow, user position, Wi-Fi fingerprint, Wireless communication, Wireless fidelity, wireless LAN
DOI10.1109/SMARTCOMP.2018.00078
Tags: 
indoor navigation
learning (artificial intelligence)
radionavigation
telecommunication computing
wireless LAN
deep learning approach
indoor user localization
smart environments
integral part
indoor localization
smart services
user position
indoor user location
Wi-Fi fingerprint
Wireless fidelity
Machine learning
Indoor environments
Wireless communication
Cloud computing
Global Positioning System
Buildings
Indoor Localization
Machine Learning
Deep Learning
TensorFlow
Smart Environments
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The #SmartME project was born from a wish of a team of researchers in the Mobile and Distributed Systems Lab (MDSLab) at the University of Messina who, in collaboration with the Industrial Liaison Office and the Center for Information Services of the University (CIAM), are eager to encourage, in an innovative fashion, a “conversation” with the municipality of Messina,  ... read more.

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