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A Transfer Learning Framework for Anomaly Detection Using Model of
  Normality

A Transfer Learning Framework for Anomaly Detection Using Model of Normality

IEEE Annual Information Technology, Electronics and Mobile Communication Conference (ITEMC), 2020
12 November 2020
Sulaiman A. Aburakhia
Tareq Tayeh
Ryan Myers
Abdallah Shami
ArXiv (abs)PDFHTML

Papers citing "A Transfer Learning Framework for Anomaly Detection Using Model of Normality"

12 / 12 papers shown
On the Intersection of Signal Processing and Machine Learning: A Use
  Case-Driven Analysis Approach
On the Intersection of Signal Processing and Machine Learning: A Use Case-Driven Analysis Approach
Sulaiman A. Aburakhia
Abdallah Shami
G. Karagiannidis
282
15
0
25 Mar 2024
Optimized Ensemble Model Towards Secured Industrial IoT Devices
Optimized Ensemble Model Towards Secured Industrial IoT DevicesAutomation, Control, and Information Technology (ACIT), 2023
MohammadNoor Injadat
202
5
0
10 Jan 2024
Tight Rates in Supervised Outlier Transfer Learning
Tight Rates in Supervised Outlier Transfer LearningInternational Conference on Learning Representations (ICLR), 2023
Mohammadreza M. Kalan
Samory Kpotufe
159
4
0
07 Oct 2023
Systemization of Knowledge (SoK)- Cross Impact of Transfer Learning in
  Cybersecurity: Offensive, Defensive and Threat Intelligence Perspectives
Systemization of Knowledge (SoK)- Cross Impact of Transfer Learning in Cybersecurity: Offensive, Defensive and Threat Intelligence Perspectives
Sofiya Makar
Ali Dehghantanha
Fattane Zarrinkalam
Gautam Srivastava
Abbas Yazdinejad
AAML
165
1
0
12 Sep 2023
Transfer Learning as an Essential Tool for Digital Twins in Renewable
  Energy Systems
Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems
C. Nivarthi
125
5
0
09 Mar 2022
An Attention-based ConvLSTM Autoencoder with Dynamic Thresholding for
  Unsupervised Anomaly Detection in Multivariate Time Series
An Attention-based ConvLSTM Autoencoder with Dynamic Thresholding for Unsupervised Anomaly Detection in Multivariate Time SeriesMachine Learning and Knowledge Extraction (MLKE), 2022
Tareq Tayeh
Sulaiman A. Aburakhia
Ryan Myers
Abdallah Shami
AI4TS
309
57
0
23 Jan 2022
A Critical Study on the Recent Deep Learning Based Semi-Supervised Video
  Anomaly Detection Methods
A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods
M. Baradaran
R. Bergevin
307
26
0
02 Nov 2021
An Automated Data Engineering Pipeline for Anomaly Detection of IoT
  Sensor Data
An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data
Xinze Li
Baixi Zou
190
7
0
28 Sep 2021
Multi-Perspective Content Delivery Networks Security Framework Using
  Optimized Unsupervised Anomaly Detection
Multi-Perspective Content Delivery Networks Security Framework Using Optimized Unsupervised Anomaly DetectionIEEE Transactions on Network and Service Management (TNSM), 2021
Li Yang
Abdallah Moubayed
Abdallah Shami
P. Heidari
Amine Boukhtouta
Adel Larabi
Richard Brunner
Stere Preda
D. Migault
231
37
0
24 Jul 2021
Anomaly Detection in Smart Manufacturing with an Application Focus on
  Robotic Finishing Systems: A Review
Anomaly Detection in Smart Manufacturing with an Application Focus on Robotic Finishing Systems: A Review
Tareq Tayeh
Abdallah Shami
314
0
0
11 Jul 2021
Distance-Based Anomaly Detection for Industrial Surfaces Using Triplet
  Networks
Distance-Based Anomaly Detection for Industrial Surfaces Using Triplet Networks
Tareq Tayeh
Sulaiman A. Aburakhia
Ryan Myers
Abdallah Shami
209
34
0
09 Nov 2020
Multi-Stage Optimized Machine Learning Framework for Network Intrusion
  Detection
Multi-Stage Optimized Machine Learning Framework for Network Intrusion DetectionIEEE Transactions on Network and Service Management (TNSM), 2020
MohammadNoor Injadat
Abdallah Moubayed
Ali Bou Nassif
Abdallah Shami
232
212
0
09 Aug 2020
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