Survey on Novelty Detection using Machine Learning Techniques
Author:
Publisher
ASTES Journal
Subject
Management of Technology and Innovation,Physics and Astronomy (miscellaneous),Engineering (miscellaneous)
Link
https://www.astesj.com/publications/ASTESJ_060510.pdf
Reference60 articles.
1. M. Amorim, F.D. Bortoloti, P.M. Ciarelli, E.O.T. Salles, D.C. Cavalieri, "Novelty Detection in Social Media by Fusing Text and Image Into a Single Structure," IEEE Access, 7, 132786-132802, 2019, doi:10.1109/ACCESS.2019.2939736.
2. E. Angola, "Novelty detection of rotating machinery using a non-parametric machine learning approach," in 2017 IEEE International Conference on Prognostics and Health Management (ICPHM), 48-54, 2017, doi:10.1109/ICPHM.2017.7998304.
3. A. Armel, D. Zaidouni, "Fraud Detection Using Apache Spark," in 2019 5th International Conference on Optimization and Applications (ICOA), IEEE, Kenitra, Morocco: 1-6, 2019, doi:10.1109/ICOA.2019.8727610.
4. L.E. Baum, T. Petrie, G. Soules, N. Weiss, "A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains," The Annals of Mathematical Statistics, 41(1), 164-171, 1970.
5. J.A. Carino, M. Delgado-Prieto, D. Zurita, M. Millan, J.A.O. Redondo, R. Romero-Troncoso, "Enhanced Industrial Machinery Condition Monitoring Methodology Based on Novelty Detection and Multi-Modal Analysis," IEEE Access, 4, 7594-7604, 2016, doi:10.1109/ACCESS.2016.2619382.
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