Improving RSS fingerprint-based localization using directional antennas
Conference item
Kanaris, Loizos, Kokkinis, Akis, Raspopoulos, Marios, Liotta, Antonio and Stavrou, Stavros 2014. Improving RSS fingerprint-based localization using directional antennas. IEEE. https://doi.org/10.1109/EuCAP.2014.6902090
Authors | Kanaris, Loizos, Kokkinis, Akis, Raspopoulos, Marios, Liotta, Antonio and Stavrou, Stavros |
---|---|
Year | 2014 |
Journal | Antennas and Propagation (EuCAP), 2014 8th European Conference on |
Publisher | IEEE |
Digital Object Identifier (DOI) | https://doi.org/10.1109/EuCAP.2014.6902090 |
Web address (URL) | http://hdl.handle.net/10545/622620 |
hdl:10545/622620 | |
Publication dates | 2014 |
Publication process dates | |
Deposited | 25 Apr 2018, 09:20 |
Permalink -
https://repository.derby.ac.uk/item/9227w/improving-rss-fingerprint-based-localization-using-directional-antennas
17
total views0
total downloads1
views this month0
downloads this month
Export as
Related outputs

Mobility Analysis during the 2020 Pandemic in a Touristic city: the Case of Cagliari
Ferrara, Enrico, Uras, Marco, Atzori, Luigi, Bagdasar, Ovidiu and Liotta, Antonio 2021. Mobility Analysis during the 2020 Pandemic in a Touristic city: the Case of Cagliari. IEEE. https://doi.org/10.1109/ieeeconf49204.2021.9604867
Relations Between Entropy and Accuracy Trends in Complex Artificial Neural Networks
Cavallaro, Lucia, Grassia, Marco, Fiumara, Giacomo, Mangioni, Giuseppe, De Meo, Pasquale, Carchiolo, Vincenza, Bagdasar, Ovidiu and Liotta, Antonio 2022. Relations Between Entropy and Accuracy Trends in Complex Artificial Neural Networks. in: Complex Networks & Their Applications X Springer.
Social network analysis: the use of graph distances to compare artificial and criminal networks
Ficara, Annamaria, Curreri, Francesco, Cavallaro, Lucia, De Meo, Pasquale, Fiumara, Giacomo, Bagdasar, Ovidiu and Liotta, Antonio 2021. Social network analysis: the use of graph distances to compare artificial and criminal networks. Journal of Smart Environments and Green Computing. https://doi.org/10.20517/jsegc.2021.08Embedded Data Imputation for Environmental Intelligent Sensing: A Case Study
Erhan, Laura, Di Mauro, Mario, Anjum, Ashiq, Bagdasar, Ovidiu, Song, Wei and Liotta, Antonio 2021. Embedded Data Imputation for Environmental Intelligent Sensing: A Case Study. Sensors. 21 (23), p. 7774. https://doi.org/10.3390/s21237774