All Outputs (5)

Predictive no-reference assessment of video quality (2016)
Journal Article
Torres Vega, M., Mocanu, D. C., Stavrou, S., & Liotta, A. (2017). Predictive no-reference assessment of video quality. Signal Processing: Image Communication, 52, 20-32. https://doi.org/10.1016/j.image.2016.12.001

Among the various means to evaluate the quality of video streams, lightweight No-Reference (NR) methods have low computation and may be executed on thin clients. Thus, these methods would be perfect candidates in cases of real-time quality assessment... Read More about Predictive no-reference assessment of video quality.

Impact of Transmission Power Control in multi-hop networks (2016)
Journal Article
Kotian, R., Exarchakos, G., Stavros, S., & Liotta, A. (2017). Impact of Transmission Power Control in multi-hop networks. Future Generation Computer Systems, 75, 94-107. https://doi.org/10.1016/j.future.2016.10.010

Many Transmission Power Control (TPC) algorithms have been proposed in the past, yet the conditions under which they are evaluated do not always reflect typical Internet-of-Things (IoT) scenarios. IoT networks consist of several source nodes transmit... Read More about Impact of Transmission Power Control in multi-hop networks.

A topological insight into restricted Boltzmann machines (2016)
Journal Article
Mocanu, D. C., Mocanu, E., Nguyen, P. H., Gibescu, M., & Liotta, A. (2016). A topological insight into restricted Boltzmann machines. Machine Learning, 104(2-3), 243-270. https://doi.org/10.1007/s10994-016-5570-z

Restricted Boltzmann Machines (RBMs) and models derived from them have been successfully used as basic building blocks in deep artificial neural networks for automatic features extraction, unsupervised weights initialization, but also as density esti... Read More about A topological insight into restricted Boltzmann machines.

Spatial anomaly detection in sensor networks using neighborhood information (2016)
Journal Article
Bosman, H. H., Iacca, G., Tejada, A., Wörtche, H. J., & Liotta, A. (2017). Spatial anomaly detection in sensor networks using neighborhood information. Information Fusion, 33, 41-56. https://doi.org/10.1016/j.inffus.2016.04.007

The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capability, has now matured after a decade-long research effort and technological advances in electronics and networked systems. An important remaining challen... Read More about Spatial anomaly detection in sensor networks using neighborhood information.

Sample Size Determination Algorithm for fingerprint-based indoor localization systems (2016)
Journal Article
Kanaris, L., Kokkinis, A., Fortino, G., Liotta, A., & Stavrou, S. (2016). Sample Size Determination Algorithm for fingerprint-based indoor localization systems. Computer Networks, 101, 169-177. https://doi.org/10.1016/j.comnet.2015.12.015

Provision of accurate location information is an important task in the Internet of Things (IoT) applications and scenarios. This need has boosted the research and development of fingerprint based, indoor localization systems, since GPS information is... Read More about Sample Size Determination Algorithm for fingerprint-based indoor localization systems.