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Non Technical Loses Detection - Experts Labels vs. Inspection Labels in the Learning Stage.

, , and . ICPRAM, page 624-628. SciTePress, (2014)

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NTL Detection: Overview of Classic and DNN-based Approaches on a Labeled Dataset of 311k Customers., , and . ISGT, page 1-5. IEEE, (2021)3D curvature analysis with a novel one-shot technique., , and . ICIP, page 3818-3822. IEEE, (2014)Semisupervised Approach to Non Technical Losses Detection., , , , and . CIARP, volume 8827 of Lecture Notes in Computer Science, page 698-705. Springer, (2014)Comparing Different Labeling Strategies in Anomalous Power Consumptions Detection., , and . ICPRAM (Selected Papers), volume 9443 of Lecture Notes in Computer Science, page 196-205. Springer, (2014)Performance Evaluation of an Automatic Fingerprint Classification Algorithm Adapted to a Vucetich Based Classification System., , and . AVBPA, volume 2091 of Lecture Notes in Computer Science, page 259-265. Springer, (2001)Improving Electric Fraud Detection using Class Imbalance Strategies., , , and . ICPRAM (2), page 135-141. SciTePress, (2012)Non Technical Loses Detection - Experts Labels vs. Inspection Labels in the Learning Stage., , and . ICPRAM, page 624-628. SciTePress, (2014)Genetic Prediction in Bovine Meat Production: Is Worth Integrating Bayesian and Machine Learning Approaches? a Comprenhensive Analysis., , and . CIARP, volume 9423 of Lecture Notes in Computer Science, page 11-18. Springer, (2015)A Statistical Approach to Reliability Estimation for Fingerprint Recognition., , , , and . BIOSIG, volume P-260 of LNI, page 183-194. GI / IEEE, (2016)Deep Generative Replay for Multivariate Time-Series Monitoring with Variational Autoencoders., , and . TMA, page 1-4. IEEE, (2023)