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Exploiting the Use of Convolutional Neural Networks for Localization in Indoor Environments
2017
Applied Artificial Intelligence
Indoor localization has been an active research area for the last two decades. A great number of sensors have been applied in the task of localization, some with high computational and energy demands, like laser beams, or with issues related to the coverage area, for example, by making use of images obtained by a network of cameras. A different approach, that presents less energy demands and a wide area of coverage, can be created by means of signal strength of wireless networks. The open issue
doi:10.1080/08839514.2017.1316592
fatcat:rmplqlepd5csdd3ly2bfybwz3u