Adapting Convolutional Neural Networks for Indoor Localization with Smart Mobile Devices

Published: May 30, 2018
Abstract
Indoor localization is emerging as an important application domain for enhanced navigation (or tracking) of people and assets in indoor locales such as buildings, malls, and underground mines. Most indoor localization solutions proposed in prior work do not deliver good accuracy without expensive infrastructure (and even then, the results may lack consistency). Ambient wireless received signal strength indication (RSSI) based fingerprinting...
Paper Details
Title
Adapting Convolutional Neural Networks for Indoor Localization with Smart Mobile Devices
Published Date
May 30, 2018
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