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Sutharshan Rajasegarar
Sutharshan Rajasegarar
Associate Professor, School of Information Technology, Deakin University
Geverifieerd e-mailadres voor unimelb.edu.au
Titel
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Jaar
High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning
SM Erfani, S Rajasegarar, S Karunasekera, C Leckie
Pattern Recognition 58, 121-134, 2016
13572016
Non-intrusive load monitoring approaches for disaggregated energy sensing: A survey
A Zoha, A Gluhak, MA Imran, S Rajasegarar
Sensors 12 (12), 16838-16866, 2012
12352012
Anomaly detection in wireless sensor networks
S Rajasegarar, C Leckie, M Palaniswami
IEEE Wireless Communications 15 (4), 34-40, 2008
3962008
Distributed anomaly detection in wireless sensor networks
S Rajasegarar, C Leckie, M Palaniswami, JC Bezdek
2006 10th IEEE Singapore international conference on communication systems, 1-5, 2006
3772006
Parking availability prediction for sensor-enabled car parks in smart cities
Y Zheng, S Rajasegarar, C Leckie
2015 IEEE tenth international conference on intelligent sensors, sensor …, 2015
3202015
Quarter sphere based distributed anomaly detection in wireless sensor networks
S Rajasegarar, C Leckie, M Palaniswami, JC Bezdek
2007 IEEE International Conference on Communications, 3864-3869, 2007
2622007
Centered hyperspherical and hyperellipsoidal one-class support vector machines for anomaly detection in sensor networks
S Rajasegarar, C Leckie, JC Bezdek, M Palaniswami
IEEE Transactions on Information Forensics and Security 5 (3), 518-533, 2010
1912010
Labelled data collection for anomaly detection in wireless sensor networks
S Suthaharan, M Alzahrani, S Rajasegarar, C Leckie, M Palaniswami
2010 sixth international conference on intelligent sensors, sensor networks …, 2010
1752010
A Hybrid Approach to Clustering in Big Data
D Kumar, JC Bezdek, M Palaniswami, S Rajasegarar, C Leckie, ...
IEEE Transactions on Cybernetics, 2015
158*2015
Anomaly detection in wireless sensor networks in a non-stationary environment
C O'Reilly, A Gluhak, MA Imran, S Rajasegarar
IEEE Communications Surveys & Tutorials 16 (3), 1413-1432, 2014
1532014
Fog-empowered anomaly detection in IoT using hyperellipsoidal clustering
L Lyu, J Jin, S Rajasegarar, X He, M Palaniswami
IEEE Internet of Things Journal 4 (5), 1174-1184, 2017
1332017
Hyperspherical cluster based distributed anomaly detection in wireless sensor networks
S Rajasegarar, C Leckie, M Palaniswami
Journal of Parallel and Distributed Computing 74 (1), 1833-1847, 2014
1312014
Bus travel time prediction with real-time traffic information
J Ma, J Chan, G Ristanoski, S Rajasegarar, C Leckie
Transportation Research Part C: Emerging Technologies 105, 536-549, 2019
1182019
Clustering ellipses for anomaly detection
M Moshtaghi, TC Havens, JC Bezdek, L Park, C Leckie, S Rajasegarar, ...
Pattern Recognition 44 (1), 55-69, 2011
1122011
Improving load forecasting based on deep learning and K-shape clustering
F Fahiman, SM Erfani, S Rajasegarar, M Palaniswami, C Leckie
2017 international joint conference on neural networks (IJCNN), 4134-4141, 2017
1052017
Elliptical anomalies in wireless sensor networks
S Rajasegarar, JC Bezdek, C Leckie, M Palaniswami
ACM Transactions on Sensor Networks (TOSN) 6 (1), 1-28, 2010
882010
Deep Metric Learning Based Citrus Disease Classification With Sparse Data
S JANARTHAN, S THUSEETHAN, S RAJASEGARAR, Q LYU, Y ZHENG, ...
IEEE Access 8, 162588-162600, 2020
832020
A scalable framework for trajectory prediction
P Rathore, D Kumar, S Rajasegarar, M Palaniswami, JC Bezdek
IEEE Transactions on Intelligent Transportation Systems 20 (10), 3860-3874, 2019
782019
Efficient unsupervised parameter estimation for one-class support vector machines
Z Ghafoori, SM Erfani, S Rajasegarar, JC Bezdek, S Karunasekera, ...
IEEE transactions on neural networks and learning systems 29 (10), 5057-5070, 2018
772018
A visual-numeric approach to clustering and anomaly detection for trajectory data
D Kumar, JC Bezdek, S Rajasegarar, C Leckie, M Palaniswami
The Visual Computer 33, 265-281, 2017
762017
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Artikelen 1–20