DDR-ID: dual deep reconstruction networks based image decomposition for anomaly detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-021-03425-0.pdf
Reference47 articles.
1. Afiq A, Zakariya M, Saad M, Nurfarzana A, Khir MHM, Fadzil A, Jale A, Gunawan W, Izuddin Z, Faizari M (2019) A review on classifying abnormal behavior in crowd scene. J Vis Commun Image Represent 58:285–303
2. Aileni RM, George S, Pasca S, Alberto VSC (2020) Data fusion-based ai algorithms in the context of iiots. Internet of Things for Industry 4.0. Springer, New York, pp 17–38
3. Amarbayasgalan T, Jargalsaikhan B, Ryu K (2018) Unsupervised novelty detection using deep autoencoders with density based clustering. Appl Sci 8(9):1468
4. An J, Cho S (2015) Variational autoencoder based anomaly detection using reconstruction probability. Special Lecture on IE 2:1–18
5. Bengio Y, Courville A, Vincent P (2013) Representation learning: a review and new perspectives. IEEE Trans Pattern Anal Mach Intell 35(8):1798–1828
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