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Research Article
Anomaly Detection Using Auto encoders
Deepak Kumar C R1
Guhanesvar M2
Tilak Vijayaraghavan S3
Jona .J.B4
Gunasekaran S.A5
123 M.Sc. (integrated) Decision and computing Science, Coimbatore Institute of Technology, Coimbatore, India. 4 Associate, Professor, Department of Computer Applications, Coimbatore Institute of Technology, Coimbatore, India. 5Assistant Professor, Department of Computer Applications, Coimbatore Institute of Technology, Coimbatore, India.
Published Online: May-June 2022
Pages: 461-468
Cite this article
No DOIReferences
[1]. JunhaiZhai, Sufang Zhang, Junfen Chen and Qiang He authored Autoencoder and its various variants published 2018 IEEE International Conference on
Systems, Man, and Cybernetics (SMC)2019
[2]. João Pereira and Margarida Silveira authouredUnsupervised representation learning and anomaly detection in ECG sequences published in
2019 International Journal of Data Mining andBioInformatics Vol.22, No. 4
[3]. C. Venkatesan; P. Karthigaikumar; Anand Paul; S. Satheeskumaran; R. Kumaranalyszed ECG Signal Preprocessing and SVM Classifier-Based
Abnormality Detection in Remote Healthcare Applications published in IEEE Access(Volume:6)2018
[4]. J. A Uriguen and B. Garcia-Zapirain "EEG artifact removal-state-of-the-art and guidelines" J Neural Eng. vol. 12 no. 3 June 2015.
[5]. Jinwon An and Sungzoon Cho lectured “Variational Autoencoder based Anomaly Detection using Reconstruction Probability” at SNU Data mining center, 2015
[6]. D. Tax and R. Duin "Outliers and data descriptions" Proc. 7th Annual Conf. Advanced School for Computing and Imaging (ASCI) 2001
[7]. V. J. Hodge and J. Austin "A survey of outlier detection methodologies" Artificial Intelligence Review vol. 22 2004.
[8]. M. Allvlahamdy and H. Bryan Riley "Performance Study of Different Denoising Methods for ECG Signals" Proceedings The 4th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2014) pp. 325-332 2014.
[9]. Hu ZhengbingSu Jun V. Jotsov O. Kochan M. Mykyichuk R. Kochan et al. "“Data Science Applications to Improve Accuracy of Thermocouples" Proceedings of the IEEE 8th International Conference on Intelligent Systems (IS-2016) pp. 180-188 2016.
[10]. LT. Jolliffe Principal Component Analysis Series: Springer Series in Statistics NY:Springer vol. XXIX pp. 487 2002.
Systems, Man, and Cybernetics (SMC)2019
[2]. João Pereira and Margarida Silveira authouredUnsupervised representation learning and anomaly detection in ECG sequences published in
2019 International Journal of Data Mining andBioInformatics Vol.22, No. 4
[3]. C. Venkatesan; P. Karthigaikumar; Anand Paul; S. Satheeskumaran; R. Kumaranalyszed ECG Signal Preprocessing and SVM Classifier-Based
Abnormality Detection in Remote Healthcare Applications published in IEEE Access(Volume:6)2018
[4]. J. A Uriguen and B. Garcia-Zapirain "EEG artifact removal-state-of-the-art and guidelines" J Neural Eng. vol. 12 no. 3 June 2015.
[5]. Jinwon An and Sungzoon Cho lectured “Variational Autoencoder based Anomaly Detection using Reconstruction Probability” at SNU Data mining center, 2015
[6]. D. Tax and R. Duin "Outliers and data descriptions" Proc. 7th Annual Conf. Advanced School for Computing and Imaging (ASCI) 2001
[7]. V. J. Hodge and J. Austin "A survey of outlier detection methodologies" Artificial Intelligence Review vol. 22 2004.
[8]. M. Allvlahamdy and H. Bryan Riley "Performance Study of Different Denoising Methods for ECG Signals" Proceedings The 4th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2014) pp. 325-332 2014.
[9]. Hu ZhengbingSu Jun V. Jotsov O. Kochan M. Mykyichuk R. Kochan et al. "“Data Science Applications to Improve Accuracy of Thermocouples" Proceedings of the IEEE 8th International Conference on Intelligent Systems (IS-2016) pp. 180-188 2016.
[10]. LT. Jolliffe Principal Component Analysis Series: Springer Series in Statistics NY:Springer vol. XXIX pp. 487 2002.
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