School of Informatics AUTh
A. Lentzas and D. Vrakas, "LadyBug. An Intensity based Localization Bug Algorithm," 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vienna, Austria, 2020, pp. 682-689.
C. Nalmpantis, D. Vrakas, On time series representations for multi-label NILM, Neural Computing and Applications, DOI: 10.1007/s00521-020-04916-5, 2020
A. Lentzas, D. Vrakas, Non-intrusive human activity recognition and abnormal behavior detection on elderly people: a review. Artif Intell Rev 53, 1975–2021, 2020
Nalmpantis C., Vrakas D. (2019) Signal2Vec: Time Series Embedding Representation. In: Macintyre J., Iliadis L., Maglogiannis I., Jayne C. (eds) Engineering Applications of Neural Networks. EANN 2019. Communications in Computer and Information Science, vol 1000. Springer, Cham
Kyrkou L., Nalmpantis C., Vrakas D. (2019) Imaging Time-Series for NILM. In: Macintyre J., Iliadis L., Maglogiannis I., Jayne C. (eds) Engineering Applications of Neural Networks. EANN 2019. Communications in Computer and Information Science, vol 1000. Springer, Cham
Symeonidis N., Nalmpantis C., Vrakas D. (2019) A Benchmark Framework to Evaluate Energy Disaggregation Solutions. In: Macintyre J., Iliadis L., Maglogiannis I., Jayne C. (eds) Engineering Applications of Neural Networks. EANN 2019. Communications in Computer and Information Science, vol 1000. Springer, Cham
C. Nalmpantis, A. Lentzas and D. Vrakas, "A Theoretical Analysis of Pooling Operation Using Information Theory," 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), Portland, OR, USA, 2019, pp. 1729-1733
A. Lentzas, C. Nalmpantis, D. Vrakas (2019) Hyperparameter Tuning using Quantum Genetic Algorithms. In: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), Portland, OR, USA, 2019, pp. 1412-1416.
A. Lentzas, A. Agapitos, D. Vrakas (2019). Evaluating state-of-the-art classifiers for human activity recognition using smartphones. In: 3rd IET International Conference on Technologies for Active and Assisted Living (TechAAL 2019).
C. Nalmpantis, D. Vrakas, Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparation, Artificial Intelligence Review, 2018
