Pipeline Leak Detection in Noisy Environment. - Georgios-Panagiotis Kousiopoulos; Georgios-Napoleon Papastavrou; Nikolaos Karagiorgos; Spyridon Nikolaidis 001; Dimitrios Porlidas (MOCAST, 2019)

Defining thresholds for leak detection parameters through statistical analysis of the noise in water/gas pipelines. - Dimitris Kampelopoulos; George-Napoleon Papastavrou; George-Panagiotis Kousiopoulos; Nikolaos Karagiorgos; Dimitrios Porlidas; Spyridon Nikolaidis 001 (I2MTC, 2020)

Machine Learning Model Comparison for Leak Detection in Noisy Industrial Pipelines. - Dimitris Kampelopoulos; George-Napoleon Papastavrou; George-Panagiotis Kousiopoulos; Nikolaos Karagiorgos; Sotirios K. Goudos; Spyridon Nikolaidis 001 (MOCAST, 2020)

Applying the Power Contributors Method in a complex CMOS cell. - Nikolaos Karagiorgos; Georgios-Panagiotis Kousiopoulos; Georgios-Napoleon Papastavrou; Dimitrios Kampelopoulos; Spyridon Nikolaidis 001 (MOCAST, 2020)

A Statistical Approach for Leak Monitoring of Highly Noisy Metallic Pipelines. - Dimitrios Kampelopoulos; George-Napoleon Papastavrou; Nikolaos Karagiorgos; George-Panagiotis Kousiopoulos; Dimitrios Porlidas; Vasileios Konstantakos; Spyridon Nikolaidis 001 (IEEE Trans. Instrum. Meas., 2022)

Acoustic Leak Localization Method for Pipelines in High-Noise Environment Using Time-Frequency Signal Segmentation. - Georgios-Panagiotis Kousiopoulos; Dimitrios Kampelopoulos; Nikolaos Karagiorgos; George-Napoleon Papastavrou; Vasileios Konstantakos; Spyridon Nikolaidis 001 (IEEE Trans. Instrum. Meas., 2022)