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Machine learning at the edge

Machine Learning

Machine Learning


ML techniques can be used not just to process the data sets generated by the Internet of Things, but also to manage the IoT, to detect intrusions and other anomalies, and to optimise many aspects of IoT design, such as hardware location, spectrum usage optimisation and the minimisation of power consumption.

Selected Publications

•  H. Li, R. Scaife and D. O'Brien, "LF model based glottal source parameter estimation by extended kalman filtering", Proceedings of the 20th european signal processing conference (EUSIPCO 2012), 2012.
•  E. Aboud and D. O'Brien, "Detection of malicious VBA macros using machine learning methods", Proceedings of the 26th irish conference on artificial intelligence and cognitive science (AICS 2018), 2018.
•  N. Trinh and D. O'Brien, "Generative adversarial network-based semi-supervised learning for pathological speech classification", International conference on statistical language and speech processing, 2020.
•  C. Garry and D. Molloy, "A software/hardware co-design framework for the 'Internet of Eyes'", 2019 IEEE 5th world forum on Internet of Things (WF-IoT), 2019.
•  Y. Gu, A. Zalkikar, M. Liu, L. Kelly, A. Hall, K. Daly and T. Ward, "Predicting medication adherence using ensemble learning and deep learning models with large scale healthcare data", Scientific Reports, vol. 11, pp. 1-13, no. 1, 2021.