Items where authors include "Karnezis, A."

Article

Xia, H., Zhao, X., Song, Z. et al. (7 more authors) (2026) Efficient & lightweight classification of rotor bar faults in induction motors by convolutional and spiking neural networks. IEEE Transactions on Industry Applications. pp. 1-13. ISSN 0093-9994

Plavos, D., Tsialiamanis, G. orcid.org/0000-0002-1205-4175, Karnezis, A. et al. (5 more authors) (2026) Graph-based convolutional neural networks for the classification of induction motor rotor bar faults using stator current & stray flux. IEEE Transactions on Industry Applications. ISSN 0093-9994

Karnezis, A. orcid.org/0009-0002-0180-5073, Piva, P.S. orcid.org/0000-0002-8239-970X and Gower, A.L. orcid.org/0000-0002-3229-5451 (2024) The average transmitted wave in random particulate materials. New Journal of Physics, 26 (6). 063002. ISSN 1367-2630

Proceedings Paper

George, A., Karnezis, A., Mihaylova, L. orcid.org/0000-0001-5856-2223 et al. (1 more author) (2026) 3D-PipeCLIP: Leveraging geometric-language alignment for sewer defect classification from point cloud data. In: Proceedings of the 12th 2026 International Conference on Control, Decision and Information Technologies (CoDIT 2026). 12th 2026 International Conference on Control, Decision and Information Technologies (CoDIT 2026), 13-16 Jul 2026, Bari, Italy. Institute of Electrical and Electronics Engineers (IEEE) . (In Press)

Karnezis, A., Worley, R., Anderson, S.R. et al. (3 more authors) (2026) Probabilistic pipe material classification via LiDAR-IMU data fusion. In: Proceedings of the 29th International Conference on Information Fusion (FUSION). 2026 29th International Conference on Information Fusion (FUSION), 23-26 Jun 2026, Trondheim, Norway. Institute of Electrical and Electronics Engineers (IEEE) . (In Press)

Karnezis, A., Worley, R., Blight, A. orcid.org/0000-0002-7580-5677 et al. (3 more authors) (2025) Feature Detection and Classification in Buried Pipes using LiDAR Technology. In: Geranmehr, M. and Collins, R., (eds.) CCWI 2025 Paper Repository. 21st International Computing & Control in the Water Industry Conference, 01-03 Sep 2025, Sheffield, UK. University of Sheffield .

Karnezis, A., Worley, R., Blight, A. et al. (3 more authors) (2025) Feature detection and classification in buried pipes using LiDAR technology. In: Proceedings of the The 21st International Computing & Control in the Water Industry Conference,, CCWI 2025. The 21st International Computing & Control in the Water Industry Conference,, CCWI 2025, 01-03 Sep 2025, Sheffield, UK. University of Sheffield .