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ORCIDSutharshan Rajasegarar
Surtharshan Rajasegarar
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2020 – today
- 2024
[j53]Ishara Bandara
, Sergiy Shelyag, Sutharshan Rajasegarar, Dan Dwyer, Eun-Jin Kim, Maia Angelova:
Winning With Chaos in Association Football: Spatiotemporal Event Distribution Randomness Metric for Team Performance Evaluation. IEEE Access 12: 83363-83376 (2024)- [j52]Siqi Xia, Sutharshan Rajasegarar, Lei Pan, Christopher Leckie, Sarah M. Erfani, Jeffrey Chan:
LabelGen: An Anomaly Label Generative Framework for Enhanced Graph Anomaly Detection. IEEE Access 12: 121971-121982 (2024) - [j51]Iynkaran Natgunanathan, Chandan K. Karmakar, Sutharshan Rajasegarar, Tianrui Zong:
Double-layer data-hiding mechanism for ECG signals. EURASIP J. Adv. Signal Process. 2024(1): 85 (2024) - [j50]Shucong Tian, Meng Yang, Rongling Xiong, Xingxing He, Sutharshan Rajasegarar:
A sequential multi-agent reinforcement learning framework for different action spaces. Expert Syst. Appl. 258: 125138 (2024) - [j49]Baojie Zhang, Ye Zhu, Yang Cao, Sutharshan Rajasegarar, Gang Li, Gang Liu:
Kernel-based iVAT with adaptive cluster extraction. Knowl. Inf. Syst. 66(11): 7057-7076 (2024) - [j48]Moe Hdaib, Sutharshan Rajasegarar, Lei Pan:
Quantum deep learning-based anomaly detection for enhanced network security. Quantum Mach. Intell. 6(1): 26 (2024) - [j47]Meng Yang, Yanghe Feng, Aravinda S. Rao, Sutharshan Rajasegarar, Shucong Tian, Zhengchun Zhou:
Evolving graph-based video crowd anomaly detection. Vis. Comput. 40(1): 303-318 (2024) - [c66]Ishara Bandara, Sergiy Shelyag, Sutharshan Rajasegarar, Daniel B. Dwyer, Eun-Jin Kim, Maia Angelova:
Time-Series Analysis of Ball Carrier Open-Space in Association Football. ISACE 2024: 1-17 - [i5]Shiva Raj Pokhrel, Luxing Yang, Sutharshan Rajasegarar, Gang Li:
Robust Zero Trust Architecture: Joint Blockchain based Federated learning and Anomaly Detection based Framework. CoRR abs/2406.17172 (2024) - 2023
- [j46]Meng Yang, Shucong Tian, Aravinda S. Rao, Sutharshan Rajasegarar, Marimuthu Palaniswami, Zhengchun Zhou:
An efficient deep neural model for detecting crowd anomalies in videos. Appl. Intell. 53(12): 15695-15710 (2023) - [j45]Xiaoyan Zhang, Zhengchun Zhou, Ying Han, Hua Meng, Meng Yang, Sutharshan Rajasegarar:
Deep learning-based real-time 3D human pose estimation. Eng. Appl. Artif. Intell. 119: 105813 (2023) - [j44]Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Deep3DCANN: A Deep 3DCNN-ANN framework for spontaneous micro-expression recognition. Inf. Sci. 630: 341-355 (2023) - [c65]Siqi Xia, Sutharshan Rajasegarar, Christopher Leckie, Sarah M. Erfani, Jeffrey Chan, Lei Pan:
EnSpeciVAT: Enhanced SpecieVAT for Cluster Tendency Identification in Graphs. ADMA (3) 2023: 323-337 - [c64]Moe Hdaib, Sutharshan Rajasegarar, Lei Pan:
Quantum Autoencoder Frameworks for Network Anomaly Detection. ICONIP (5) 2023: 69-82 - [c63]Baojie Zhang, Yang Cao, Ye Zhu, Sutharshan Rajasegarar, Gang Liu, Hong Xian Li, Maia Angelova, Gang Li:
An Improved Visual Assessment with Data-Dependent Kernel for Stream Clustering. PAKDD (1) 2023: 197-209 - [c62]Dominic Jack, Sarah M. Erfani, Jeffrey Chan, Sutharshan Rajasegarar, Christopher Leckie:
It's PageRank All The Way Down: Simplifying Deep Graph Networks. SDM 2023: 172-180 - 2022
- [j43]Sivasubramaniam Janarthan, Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
P2OP - Plant Pathology on Palms: A deep learning-based mobile solution for in-field plant disease detection. Comput. Electron. Agric. 202: 107371 (2022) - [j42]Jiaman Ma, Jeffrey Chan, Sutharshan Rajasegarar, Christopher Leckie:
Multi-attention graph neural networks for city-wide bus travel time estimation using limited data. Expert Syst. Appl. 202: 117057 (2022) - [j41]Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
EmoSeC: Emotion recognition from scene context. Neurocomputing 492: 174-187 (2022) - [j40]Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Deep Continual Learning for Emerging Emotion Recognition. IEEE Trans. Multim. 24: 4367-4380 (2022) - [c61]Venkata Abhishek Kanthuru, Sutharshan Rajasegarar, Punit Rathore, Robin Ram Mohan Doss, Lei Pan, Biplob Ray, Morshed Chowdhury, Chandrasekaran Srimathi, M. A. Saleem Durai:
Cyber Attack Detection in IoT Networks with Small Samples: Implementation And Analysis. ADMA (1) 2022: 118-130 - [c60]Vatsal Patel, Sutharshan Rajasegarar, Lei Pan, Jiajun Liu, Liming Zhu:
EvAnGCN: Evolving Graph Deep Neural Network Based Anomaly Detection in Blockchain. ADMA (1) 2022: 444-456 - [c59]Noorain Zaidi, Priya Kumari, Sutharshan Rajasegarar, Chandan K. Karmakar:
Machine Learning Aided Minimal Sensor based Hand Gesture Character Recognition. DSAA 2022: 1-9 - [c58]Sivasubramaniam Janarthan, Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Double Attention-Based Lightweight Network for Plant Pest Recognition. ICONIP (6) 2022: 598-611 - [c57]Siqi Xia, Sutharshan Rajasegarar, Christopher Leckie, Sarah M. Erfani, Jeffrey Chan:
Exploiting Redundancy in Network Flow Information for Efficient Security Attack Detection. NSS 2022: 105-119 - [i4]Sivasubramaniam Janarthan, Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Double Attention-based Lightweight Network for Plant Pest Recognition. CoRR abs/2210.09956 (2022) - 2021
- [j39]Guangjun Li, Preetpal Sharma, Lei Pan, Sutharshan Rajasegarar, Chandan K. Karmakar, Nicholas Charles Patterson:
Deep learning algorithms for cyber security applications: A survey. J. Comput. Secur. 29(5): 447-471 (2021) - [j38]Madhumita A. Takalkar, Selvarajah Thuseethan, Sutharshan Rajasegarar, Zenon Chaczko, Min Xu, John Yearwood:
LGAttNet: Automatic micro-expression detection using dual-stream local and global attentions. Knowl. Based Syst. 212: 106566 (2021) - [j37]Punit Rathore, Dheeraj Kumar, James C. Bezdek, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Visual Structural Assessment and Anomaly Detection for High-Velocity Data Streams. IEEE Trans. Cybern. 51(12): 5979-5992 (2021) - [j36]Morshed U. Chowdhury, Biplob Ray, Sujan Chowdhury, Sutharshan Rajasegarar:
A Novel Insider Attack and Machine Learning Based Detection for the Internet of Things. ACM Trans. Internet Things 2(4): 26:1-26:23 (2021) - [c56]Jillian Tallboys, Ye Zhu, Sutharshan Rajasegarar:
Identification of Stock Market Manipulation with Deep Learning. ADMA 2021: 408-420 - [c55]Khondker Fariha Hossain, Sharif Amit Kamran, Alireza Tavakkoli, Lei Pan, Xingjun Ma, Sutharshan Rajasegarar, Chandan Karmaker:
ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks. ICMLA 2021: 50-56 - [c54]Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Boosting Emotion Recognition in Context using Non-target Subject Information. IJCNN 2021: 1-7 - [i3]Khondker Fariha Hossain, Sharif Amit Kamran, Alireza Tavakkoli, Lei Pan, Daniel Ma, Sutharshan Rajasegarar, Chandan Karmaker:
ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks. CoRR abs/2107.07677 (2021) - 2020
- [j35]Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Complex Emotion Profiling: An Incremental Active Learning Based Approach With Sparse Annotations. IEEE Access 8: 147711-147727 (2020) - [j34]Sivasubramaniam Janarthan, Selvarajah Thuseethan, Sutharshan Rajasegarar, Qiang Lyu, Yongqiang Zheng, John Yearwood:
Deep Metric Learning Based Citrus Disease Classification With Sparse Data. IEEE Access 8: 162588-162600 (2020) - [j33]Iynkaran Natgunanathan, Chandan K. Karmakar, Sutharshan Rajasegarar, Tianrui Zong, Ahsan Habib:
Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals. IEEE Access 8: 181233-181245 (2020) - [j32]Chee Keong Ng, Sutharshan Rajasegarar, Lei Pan, Frank Jiang, Leo Yu Zhang:
VoterChoice: A ransomware detection honeypot with multiple voting framework. Concurr. Comput. Pract. Exp. 32(14) (2020) - [j31]Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Multiclass Anomaly Detector: the CS++ Support Vector Machine. J. Mach. Learn. Res. 21: 213:1-213:39 (2020) - [j30]Lei Pan, Nicholas Charles Patterson, Sophie McKenzie, Surtharshan Rajasegarar, Guy Wood-Bradley, Justin T. Rough, Wei Luo, Elicia Lanham, Jo Coldwell-Neilson:
Gathering Intelligence on Student Information Behavior Using Data Mining. Libr. Trends 68(4): 636-658 (2020) - [c53]Jiaman Ma, Jeffrey Chan, Sutharshan Rajasegarar, Goce Ristanoski, Christopher Leckie:
Multi-Attention 3D Residual Neural Network for Origin-Destination Crowd Flow Prediction. ICDM 2020: 1160-1165 - [c52]Vatsal Patel, Lei Pan, Sutharshan Rajasegarar:
Graph Deep Learning Based Anomaly Detection in Ethereum Blockchain Network. NSS 2020: 132-148 - [c51]Selvarajah Thuseethan, Sivasubramaniam Janarthan, Sutharshan Rajasegarar, Priya Kumari, John Yearwood:
Multimodal Deep Learning Framework for Sentiment Analysis from Text-Image Web Data. WI/IAT 2020: 267-274
2010 – 2019
- 2019
- [j29]Maia Angelova, Sergiy Shelyag, Sutharshan Rajasegarar, Dineshen Chuckravanen, Sujan Rajbhandari, Paul B. Gastin, Alan St Clair Gibson:
Investigation of Complexity and Regulatory Role of Physiological Activities During a Pacing Exercise. IEEE Access 7: 152334-152346 (2019) - [j28]Punit Rathore, Dheeraj Kumar, Sutharshan Rajasegarar, Marimuthu Palaniswami, James C. Bezdek:
A Scalable Framework for Trajectory Prediction. IEEE Trans. Intell. Transp. Syst. 20(10): 3860-3874 (2019) - [j27]Punit Rathore, Dheeraj Kumar, James C. Bezdek, Sutharshan Rajasegarar, Marimuthu Palaniswami:
A Rapid Hybrid Clustering Algorithm for Large Volumes of High Dimensional Data. IEEE Trans. Knowl. Data Eng. 31(4): 641-654 (2019) - [c50]Jianchao Lu, Jiaxing Wang, Xi Zheng, Chandan K. Karmakar, Sutharshan Rajasegarar:
Detection of Smoking Events from Confounding Activities of Daily Living. ACSW 2019: 39:1-39:9 - [c49]Waqas Ahmad Piracha, Morshed U. Chowdhury, Biplob Ray, Sutharshan Rajasegarar, Robin Doss:
Insider Attacks on Zigbee Based IoT Networks by Exploiting AT Commands. ATIS 2019: 77-91 - [c48]Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Deep Hybrid Spatiotemporal Networks for Continuous Pain Intensity Estimation. ICONIP (3) 2019: 449-461 - [c47]Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Emotion Intensity Estimation from Video Frames using Deep Hybrid Convolutional Neural Networks. IJCNN 2019: 1-10 - [c46]Meng Yang, Sutharshan Rajasegarar, Sarah M. Erfani, Christopher Leckie:
Deep Learning and One-class SVM based Anomalous Crowd Detection. IJCNN 2019: 1-8 - [c45]Selvarajah Thuseethan, Sutharshan Rajasegarar, John Yearwood:
Detecting Micro-expression Intensity Changes from Videos Based on Hybrid Deep CNN. PAKDD (3) 2019: 387-399 - [c44]Morshed U. Chowdhury, Robin Doss, Biplob Ray, Sutharshan Rajasegarar, Sujan Chowdhury:
IoT Insider Attack - Survey. SGIoT 2019: 28-41 - 2018
- [j26]Maia Angelova, Jeremy Ellman, Helen Gibson, Paul Oman, Sutharshan Rajasegarar, Ye Zhu:
User Activity Pattern Analysis in Telecare Data. IEEE Access 6: 33306-33317 (2018) - [j25]Punit Rathore, Aravinda S. Rao, Sutharshan Rajasegarar, Elena Vanz, Jayavardhana Gubbi, Marimuthu Palaniswami:
Real-Time Urban Microclimate Analysis Using Internet of Things. IEEE Internet Things J. 5(2): 500-511 (2018) - [j24]Punit Rathore, James C. Bezdek, Sarah M. Erfani, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Ensemble Fuzzy Clustering Using Cumulative Aggregation on Random Projections. IEEE Trans. Fuzzy Syst. 26(3): 1510-1524 (2018) - [j23]Dheeraj Kumar, Huayu Wu, Sutharshan Rajasegarar, Christopher Leckie, Shonali Krishnaswamy, Marimuthu Palaniswami:
Fast and Scalable Big Data Trajectory Clustering for Understanding Urban Mobility. IEEE Trans. Intell. Transp. Syst. 19(11): 3709-3722 (2018) - [j22]Zahra Ghafoori, Sarah M. Erfani, Sutharshan Rajasegarar, James C. Bezdek, Shanika Karunasekera, Christopher Leckie:
Efficient Unsupervised Parameter Estimation for One-Class Support Vector Machines. IEEE Trans. Neural Networks Learn. Syst. 29(10): 5057-5070 (2018) - [c43]Minh Tuan Doan, Jianzhong Qi, Sutharshan Rajasegarar, Christopher Leckie:
Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data. IEEE BigData 2018: 106-111 - [c42]Meng Yang, Lida Rashidi, Sutharshan Rajasegarar, Christopher Leckie, Aravinda S. Rao, Marimuthu Palaniswami:
Crowd Activity Change Point Detection in Videos via Graph Stream Mining. CVPR Workshops 2018: 215-223 - [c41]Meng Yang, Lida Rashidi, Aravinda S. Rao, Sutharshan Rajasegarar, Mohadeseh Ganji, Marimuthu Palaniswami, Christopher Leckie:
Cluster-Based Crowd Movement Behavior Detection. DICTA 2018: 1-8 - [c40]Punit Rathore, James C. Bezdek, Dheeraj Kumar, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Approximate Cluster Heat Maps of Large High-Dimensional Data. ICPR 2018: 195-200 - [c39]Meng Yang, Lida Rashidi, Sutharshan Rajasegarar, Christopher Leckie:
Graph Stream Mining Based Anomalous Event Analysis. PRICAI (1) 2018: 891-903 - [c38]Ahmad Shaker Abdalrada, Jemal H. Abawajy, Morshed U. Chowdhury, Sutharshan Rajasegarar, Tahsien Al-Quraishi, Herbert F. Jelinek:
Relationship Between Angiotensin Converting Enzyme Gene and Cardiac Autonomic Neuropathy Among Australian Population. SCDM 2018: 135-146 - [c37]Tahsien Al-Quraishi, Jemal H. Abawajy, Morshed U. Chowdhury, Sutharshan Rajasegarar, Ahmad Shaker Abdalrada:
Breast Cancer Recurrence Prediction Using Random Forest Model. SCDM 2018: 318-329 - [c36]Punit Rathore, Dheeraj Kumar, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Bayesian maximum entropy and interacting multiple model based automatic sensor drift detection and correction in an IoT environment. WF-IoT 2018: 598-603 - [i2]Punit Rathore, Dheeraj Kumar, Sutharshan Rajasegarar, Marimuthu Palaniswami, James C. Bezdek:
A Scalable Framework for Trajectory Prediction. CoRR abs/1806.03582 (2018) - [i1]Minh Tuan Doan, Jianzhong Qi, Sutharshan Rajasegarar, Christopher Leckie:
Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data. CoRR abs/1811.02722 (2018) - 2017
- [j21]Lingjuan Lyu, Jiong Jin, Sutharshan Rajasegarar, Xuanli He, Marimuthu Palaniswami:
Fog-Empowered Anomaly Detection in IoT Using Hyperellipsoidal Clustering. IEEE Internet Things J. 4(5): 1174-1184 (2017) - [j20]Punit Rathore, Dheeraj Kumar, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Maximum Entropy-Based Auto Drift Correction Using High- and Low-Precision Sensors. ACM Trans. Sens. Networks 13(3): 24:1-24:41 (2017) - [j19]Dheeraj Kumar, James C. Bezdek, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
A visual-numeric approach to clustering and anomaly detection for trajectory data. Vis. Comput. 33(3): 265-281 (2017) - [c35]Yuantian Miao, Lei Pan, Sutharshan Rajasegarar, Jun Zhang, Christopher Leckie, Yang Xiang:
Distributed Detection of Zero-Day Network Traffic Flows. AusDM 2017: 173-191 - [c34]Babin Bhandari, Jianchao Lu, Xi Zheng, Sutharshan Rajasegarar, Chandan K. Karmakar:
Non-invasive sensor based automated smoking activity detection. EMBC 2017: 845-848 - [c33]Fateme Fahiman, Sarah M. Erfani, Sutharshan Rajasegarar, Marimuthu Palaniswami, Christopher Leckie:
Improving load forecasting based on deep learning and K-shape clustering. IJCNN 2017: 4134-4141 - [c32]Aoi Honda, Simon James, Sutharshan Rajasegarar:
Orness and Cardinality Indices for Averaging Inclusion-Exclusion Integrals. MDAI 2017: 51-62 - [c31]Goce Ristanoski, Rahul Soni, Sutharshan Rajasegarar, James Bailey, Christopher Leckie:
Clustering Aided Support Vector Machines. MLDM 2017: 322-334 - 2016
- [j18]Sarah M. Erfani, Sutharshan Rajasegarar, Shanika Karunasekera, Christopher Leckie:
High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning. Pattern Recognit. 58: 121-134 (2016) - [j17]Dheeraj Kumar, James C. Bezdek, Marimuthu Palaniswami, Sutharshan Rajasegarar, Christopher Leckie, Timothy Craig Havens:
A Hybrid Approach to Clustering in Big Data. IEEE Trans. Cybern. 46(10): 2372-2385 (2016) - [j16]Dheeraj Kumar, James C. Bezdek, Sutharshan Rajasegarar, Marimuthu Palaniswami, Christopher Leckie, Jeffrey Chan, Jayavardhana Gubbi:
Adaptive Cluster Tendency Visualization and Anomaly Detection for Streaming Data. ACM Trans. Knowl. Discov. Data 11(2): 24:1-24:40 (2016) - [c30]Meng Yang, Sutharshan Rajasegarar, Aravinda S. Rao, Christopher Leckie, Marimuthu Palaniswami:
Anomalous Behavior Detection in Crowded Scenes Using Clustering and Spatio-Temporal Features. Intelligent Information Processing 2016: 132-141 - [c29]Zahra Ghafoori, Sarah M. Erfani, Sutharshan Rajasegarar, Shanika Karunasekera, Christopher A. Leckie:
Anomaly detection in non-stationary data: Ensemble based self-adaptive OCSVM. IJCNN 2016: 2476-2483 - [c28]Zahra Ghafoori, Sutharshan Rajasegarar, Sarah M. Erfani, Shanika Karunasekera, Christopher A. Leckie:
Unsupervised Parameter Estimation for One-Class Support Vector Machines. PAKDD (2) 2016: 183-195 - [c27]Junying Chen, Sutharshan Rajasegarar, Christopher Leckie, André F. Gygax:
Pedestrian behaviour analysis using the microsoft kinect. PerCom Workshops 2016: 1-6 - [c26]Lida Rashidi, Andrey Kan, James Bailey, Jeffrey Chan, Christopher Leckie, Wei Liu, Sutharshan Rajasegarar, Kotagiri Ramamohanarao:
Node Re-Ordering as a Means of Anomaly Detection in Time-Evolving Graphs. ECML/PKDD (2) 2016: 162-178 - [c25]Sarah M. Erfani, Mahsa Baktashmotlagh, Sutharshan Rajasegarar, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao:
R1STM: One-class Support Tensor Machine with Randomised Kernel. SDM 2016: 198-206 - 2015
- [j15]Dheeraj Kumar, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Geospatial Estimation-Based Auto Drift Correction in Wireless Sensor Networks. ACM Trans. Sens. Networks 11(3): 50:1-50:39 (2015) - [c24]Sarah M. Erfani, Mahsa Baktashmotlagh, Sutharshan Rajasegarar, Shanika Karunasekera, Christopher Leckie:
R1SVM: A Randomised Nonlinear Approach to Large-Scale Anomaly Detection. AAAI 2015: 432-438 - [c23]Minh Tuan Doan, Sutharshan Rajasegarar, Mahsa Salehi, Masud Moshtaghi, Christopher Leckie:
Profiling Pedestrian Distribution and Anomaly Detection in a Dynamic Environment. CIKM 2015: 1827-1830 - [c22]Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
Pattern based anomalous user detection in cognitive radio networks. ICASSP 2015: 5605-5609 - [c21]Yanxu Zheng, Sutharshan Rajasegarar, Christopher Leckie:
Parking availability prediction for sensor-enabled car parks in smart cities. ISSNIP 2015: 1-6 - [c20]Lida Rashidi, Sutharshan Rajasegarar, Christopher Leckie:
An Embedding Scheme for Detecting Anomalous Block Structured Graphs. PAKDD (2) 2015: 215-227 - [c19]Alistair Shilton, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
DP1SVM: A dynamic planar one-class support vector machine for Internet of Things environment. RIoT 2015: 1-6 - 2014
- [j14]Masud Moshtaghi, Christopher Leckie, Shanika Karunasekera, Sutharshan Rajasegarar:
An adaptive elliptical anomaly detection model for wireless sensor networks. Comput. Networks 64: 195-207 (2014) - [j13]Colin O'Reilly, Alexander Gluhak, Muhammad Ali Imran, Sutharshan Rajasegarar:
Anomaly Detection in Wireless Sensor Networks in a Non-Stationary Environment. IEEE Commun. Surv. Tutorials 16(3): 1413-1432 (2014) - [j12]Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
Hyperspherical cluster based distributed anomaly detection in wireless sensor networks. J. Parallel Distributed Comput. 74(1): 1833-1847 (2014) - [j11]Sutharshan Rajasegarar, Alexander Gluhak, Muhammad Ali Imran, Michele Nati, Masud Moshtaghi, Christopher Leckie, Marimuthu Palaniswami:
Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks. Pattern Recognit. 47(9): 2867-2879 (2014) - [j10]Sutharshan Rajasegarar, Timothy C. Havens, Shanika Karunasekera, Christopher Leckie, James C. Bezdek, Milan Jamriska, Ajith Gunatilaka, Alex Skvortsov, Marimuthu Palaniswami:
High-Resolution Monitoring of Atmospheric Pollutants Using a System of Low-Cost Sensors. IEEE Trans. Geosci. Remote. Sens. 52(7): 3823-3832 (2014) - [j9]Masud Moshtaghi, James C. Bezdek, Timothy C. Havens, Christopher Leckie, Shanika Karunasekera, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Streaming analysis in wireless sensor networks. Wirel. Commun. Mob. Comput. 14(9): 905-921 (2014) - [c18]Aravinda S. Rao, Jayavardhana Gubbi, Sutharshan Rajasegarar, Slaven Marusic, Marimuthu Palaniswami:
Detection of Anomalous Crowd Behaviour Using Hyperspherical Clustering. DICTA 2014: 1-8 - [c17]Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
Spatio-temporal estimation with Bayesian maximum entropy and compressive sensing in communication constrained networks. ICC 2014: 4536-4541 - [c16]Sutharshan Rajasegarar, Peng Zhang, Yang Zhou, Shanika Karunasekera, Christopher Leckie, Marimuthu Palaniswami:
High resolution spatio-temporal monitoring of air pollutants using wireless sensor networks. ISSNIP 2014: 1-6 - [c15]Lida Rashidi, Sutharshan Rajasegarar, Christopher Leckie, Michele Nati, Alexander Gluhak, Muhammad Ali Imran, Marimuthu Palaniswami:
Profiling spatial and temporal behaviour in sensor networks: A case study in energy monitoring. ISSNIP 2014: 1-7 - [c14]Yanxu Zheng, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
Smart car parking: Temporal clustering and anomaly detection in urban car parking. ISSNIP 2014: 1-6 - 2013
- [c13]Dheeraj Kumar, Marimuthu Palaniswami, Sutharshan Rajasegarar, Christopher Leckie, James C. Bezdek, Timothy C. Havens:
clusiVAT: A mixed visual/numerical clustering algorithm for big data. IEEE BigData 2013: 112-117 - [c12]Andrea Pirisi, Francesco Grimaccia, Marco Mussetta, Riccardo Enrico Zich, Ron Johnstone, Marimuthu Palaniswami, Sutharshan Rajasegarar:
Optimization of an energy harvesting buoy for coral reef monitoring. IEEE Congress on Evolutionary Computation 2013: 629-634 - [c11]Dheeraj Kumar, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Automatic Sensor Drift Detection and Correction Using Spatial Kriging and Kalman Filtering. DCOSS 2013: 183-190 - [c10]Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Combined multiclass classification and anomaly detection for large-scale Wireless Sensor Networks. ISSNIP 2013: 491-496 - 2012
- [j8]Ahmed Zoha, Alexander Gluhak, Muhammad Ali Imran, Sutharshan Rajasegarar:
Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey. Sensors 12(12): 16838-16866 (2012) - [c9]Sutharshan Rajasegarar, James C. Bezdek, Masud Moshtaghi, Christopher Leckie, Timothy C. Havens, Marimuthu Palaniswami:
Measures for clustering and anomaly detection in sets of higher dimensional ellipsoids. IJCNN 2012: 1-8 - [c8]Ahmed Zoha, Alexander Gluhak, Michele Nati, Muhammad Ali Imran, Sutharshan Rajasegarar:
Acoustic and device feature fusion for load recognition. IEEE Conf. of Intelligent Systems 2012: 386-392 - [c7]Colin O'Reilly, Alexander Gluhak, Muhammad Ali Imran, Sutharshan Rajasegarar:
Online anomaly rate parameter tracking for anomaly detection in wireless sensor networks. SECON 2012: 191-199 - 2011
- [j7]James C. Bezdek, Sutharshan Rajasegarar, Masud Moshtaghi, Christopher Leckie, Marimuthu Palaniswami, Timothy C. Havens:
Anomaly Detection in Environmental Monitoring Networks [Application Notes]. IEEE Comput. Intell. Mag. 6(2): 52-58 (2011) - [j6]Maen Takruri, Sutharshan Rajasegarar, Subhash Challa, Christopher Leckie, Marimuthu Palaniswami:
Spatio-temporal modelling-based drift-aware wireless sensor networks. IET Wirel. Sens. Syst. 1(2): 110-122 (2011) - [j5]Masud Moshtaghi, Timothy C. Havens, James C. Bezdek, Laurence Anthony F. Park, Christopher Leckie, Sutharshan Rajasegarar, James M. Keller, Marimuthu Palaniswami:
Clustering ellipses for anomaly detection. Pattern Recognit. 44(1): 55-69 (2011) - [j4]Masud Moshtaghi, Sutharshan Rajasegarar, Christopher Leckie, Shanika Karunasekera:
An efficient hyperellipsoidal clustering algorithm for resource-constrained environments. Pattern Recognit. 44(9): 2197-2209 (2011) - [c6]Masud Moshtaghi, Christopher Leckie, Shanika Karunasekera, James C. Bezdek, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Incremental Elliptical Boundary Estimation for Anomaly Detection in Wireless Sensor Networks. ICDM 2011: 467-476 - [c5]Sarah M. Erfani, Sutharshan Rajasegarar, Christopher Leckie:
An efficient approach to detecting concept-evolution in network data streams. ATNAC 2011: 1-7 - 2010
- [j3]Sutharshan Rajasegarar, Christopher Leckie, James C. Bezdek, Marimuthu Palaniswami:
Centered hyperspherical and hyperellipsoidal one-class support vector machines for anomaly detection in sensor networks. IEEE Trans. Inf. Forensics Secur. 5(3): 518-533 (2010) - [c4]Shan Suthaharan, Christopher Leckie, Masud Moshtaghi, Shanika Karunasekera, Sutharshan Rajasegarar:
Sensor data boundary estimation for anomaly detection in wireless sensor networks. MASS 2010: 546-551
2000 – 2009
- 2009
- [j2]Sutharshan Rajasegarar, James C. Bezdek, Christopher Leckie, Marimuthu Palaniswami:
Elliptical anomalies in wireless sensor networks. ACM Trans. Sens. Networks 6(1): 7:1-7:28 (2009) - 2008
- [j1]Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
Anomaly detection in wireless sensor networks. IEEE Wirel. Commun. 15(4): 34-40 (2008) - [c3]Maen Takruri, Sutharshan Rajasegarar, Subhash Challa, Christopher Leckie, Marimuthu Palaniswami:
Online drift correction in wireless sensor networks using spatio-temporal modeling. FUSION 2008: 1-8 - [c2]Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
CESVM: Centered Hyperellipsoidal Support Vector Machine Based Anomaly Detection. ICC 2008: 1610-1614 - 2007
- [c1]Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami, James C. Bezdek:
Quarter Sphere Based Distributed Anomaly Detection in Wireless Sensor Networks. ICC 2007: 3864-3869
Coauthor Index
Christopher Leckie
aka: Christopher A. Leckie
aka: Christopher A. Leckie
[j52] [c65] [c62] [j42] [c57] [c53] [c46] [j23] [j22] [c43] [c42] [c41] [c39] [i1] [j19] [c35] [c33] [c31] [j18] [j17] [j16] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [j14] [j12] [j11] [j10] [j9] [c17] [c16] [c15] [c14] [c13] [c9] [j7] [j6] [j5] [j4] [c6] [c5] [j3] [c4] [j2] [j1] [c3] [c2] [c1]
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