scholarly journals A Deep Learning Approach for Network Anomaly Detection Based on AMF-LSTM

2018 ◽  
pp. 137-141 ◽  
Author(s):  
Mingyi Zhu ◽  
Kejiang Ye ◽  
Yang Wang ◽  
Cheng-Zhong Xu
Keyword(s):  
Deep Learning ◽  
Anomaly Detection ◽  
Learning Approach ◽  
Network Anomaly Detection

scholarly journals A Deep Learning Approach to Anomaly Detection in the Gaia Space Mission Data

2019 ◽  
pp. 390-401
Author(s):  
Alessandro Druetto ◽  
Marco Roberti ◽  
Rossella Cancelliere ◽  
Davide Cavagnino ◽  
Mario Gai
Keyword(s):  
Deep Learning ◽  
Anomaly Detection ◽  
Space Mission ◽  
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Sensor Data-Driven UAV Anomaly Detection using Deep Learning Approach

2021 ◽  
Author(s):  
Julio Galvan ◽  
Ashok Raja ◽  
Yanyan Li ◽  
Jiawei Yuan
Keyword(s):  
Deep Learning ◽  
Anomaly Detection ◽  
Data Driven ◽  
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scholarly journals A Deep Learning Approach to Anomaly Detection in Nuclear Reactors

2018 ◽  
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Francesco Caliva ◽  
Fabio Sousa De Ribeiro ◽  
Antonios Mylonakis ◽  
Christophe Demazirere ◽  
Paolo Vinai ◽  
...  
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Deep Learning ◽  
Anomaly Detection ◽  
Nuclear Reactors ◽  
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scholarly journals A deep learning approach for anomaly detection with industrial time series data: a refrigerators manufacturing case study

2019 ◽  
Vol 38 ◽  
pp. 233-240 ◽  
Author(s):  
Mattia Carletti ◽  
Chiara Masiero ◽  
Alessandro Beghi ◽  
Gian Antonio Susto
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Time Series ◽  
Deep Learning ◽  
Anomaly Detection ◽  
Time Series Data ◽  
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scholarly journals DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 1991-2005 ◽  
Author(s):  
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Shoaib Ahmed Siddiqui ◽  
Andreas Dengel ◽  
Sheraz Ahmed
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Anomaly Detection ◽  
Learning Approach ◽  
Unsupervised Anomaly Detection
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