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Sutharshan Rajasegarar
Sutharshan Rajasegarar
School of Information Technology, Deakin University
Geverifieerd e-mailadres voor unimelb.edu.au
Titel
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Jaar
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
11332012
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
11212016
Anomaly detection in wireless sensor networks
S Rajasegarar, C Leckie, M Palaniswami
IEEE Wireless Communications 15 (4), 34-40, 2008
3712008
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
3692006
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
2932015
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
2512007
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
1792010
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
1602010
A Hybrid Approach to Clustering in Big Data
D Kumar, JC Bezdek, M Palaniswami, S Rajasegarar, C Leckie, ...
IEEE Transactions on Cybernetics, 2015
149*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
1352014
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
1222017
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
1182014
Clustering ellipses for anomaly detection
M Moshtaghi, TC Havens, JC Bezdek, L Park, C Leckie, S Rajasegarar, ...
Pattern Recognition 44 (1), 55-69, 2011
1072011
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
922017
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
842019
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
842010
Ensemble fuzzy clustering using cumulative aggregation on random projections
P Rathore, JC Bezdek, SM Erfani, S Rajasegarar, M Palaniswami
IEEE transactions on fuzzy systems 26 (3), 1510-1524, 2017
692017
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
652017
Anomaly detection by clustering ellipsoids in wireless sensor networks
M Moshtaghi, S Rajasegarar, C Leckie, S Karunasekera
2009 international conference on intelligent sensors, sensor networks and …, 2009
652009
Real-time urban microclimate analysis using internet of things
P Rathore, AS Rao, S Rajasegarar, E Vanz, J Gubbi, M Palaniswami
IEEE Internet of Things Journal 5 (2), 500-511, 2017
642017
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Artikelen 1–20