Sutharshan Rajasegarar

发表

Combined multiclass classification and anomaly detection for large-scale Wireless Sensor Networks

Marimuthu Palaniswami, Alistair Shilton, Sutharshan Rajasegarar, 2013, 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

Optimization of an energy harvesting buoy for coral reef monitoring

Marimuthu Palaniswami, Francesco Grimaccia, Marco Mussetta, 2013, 2013 IEEE Congress on Evolutionary Computation.

Maximum Entropy-Based Auto Drift Correction Using High- and Low-Precision Sensors

Marimuthu Palaniswami, Dheeraj Kumar, Sutharshan Rajasegarar, 2017, ACM Trans. Sens. Networks.

High resolution spatio-temporal monitoring of air pollutants using wireless sensor networks

Peng Zhang, Marimuthu Palaniswami, Christopher Leckie, 2014, 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data

Christopher Leckie, Sutharshan Rajasegarar, Jianzhong Qi, 2018, 2018 IEEE International Conference on Big Data (Big Data).

R1STM: One-class Support Tensor Machine with Randomised Kernel

James Bailey, Vinh Nguyen, Kotagiri Ramamohanarao, 2016, SDM.

Insider Attacks on Zigbee Based IoT Networks by Exploiting AT Commands

Sutharshan Rajasegarar, Morshed U. Chowdhury, Robin Doss, 2019, ATIS.

Anomaly detection by clustering ellipsoids in wireless sensor networks

Sutharshan Rajasegarar, Shanika Karunasekera, Masud Moshtaghi, 2009, 2009 International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

Graph Stream Mining Based Anomalous Event Analysis

Christopher Leckie, Sutharshan Rajasegarar, Lida Rashidi, 2018, PRICAI.

Approximate Cluster Heat Maps of Large High-Dimensional Data

Marimuthu Palaniswami, James C. Bezdek, Dheeraj Kumar, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

An adaptive elliptical anomaly detection model for wireless sensor networks

Christopher Leckie, Sutharshan Rajasegarar, Shanika Karunasekera, 2014, Comput. Networks.

Multiclass Anomaly Detector: the CS plus plus Support Vector Machine

Marimuthu Palaniswami, Sutharshan Rajasegarar, Alistair Shilton, 2020 .

Deep Learning and One-class SVM based Anomalous Crowd Detection

Sutharshan Rajasegarar, Christopher Leckie, Meng Yang, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Visual Structural Assessment and Anomaly Detection for High-Velocity Data Streams.

Marimuthu Palaniswami, Sutharshan Rajasegarar, Punit Rathore, 2020, IEEE transactions on cybernetics.

Online drift correction in wireless sensor networks using spatio-temporal modeling

Marimuthu Palaniswami, Christopher Leckie, Subhash Challa, 2008, 2008 11th International Conference on Information Fusion.

A Scalable Framework for Trajectory Prediction

Marimuthu Palaniswami, James C. Bezdek, Dheeraj Kumar, 2018, IEEE Transactions on Intelligent Transportation Systems.

Pedestrian behaviour analysis using the microsoft kinect

Christopher Leckie, Junying Chen, Sutharshan Rajasegarar, 2016, 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops).

Graph Deep Learning Based Anomaly Detection in Ethereum Blockchain Network

Lei Pan, Sutharshan Rajasegarar, Vatsal Patel, 2020, NSS.

Clustering Aided Support Vector Machines

James Bailey, Sutharshan Rajasegarar, Christopher Leckie, 2017, MLDM.

Bus travel time prediction with real-time traffic information

Christopher Leckie, Sutharshan Rajasegarar, Jeffrey Chan, 2019, Transportation Research Part C: Emerging Technologies.

Distributed Detection of Zero-Day Network Traffic Flows

Jun Zhang, Christopher Leckie, Sutharshan Rajasegarar, 2017, AusDM.

An Embedding Scheme for Detecting Anomalous Block Structured Graphs

Christopher Leckie, Sutharshan Rajasegarar, Lida Rashidi, 2015, PAKDD.

Emotion Intensity Estimation from Video Frames using Deep Hybrid Convolutional Neural Networks

John Yearwood, Sutharshan Rajasegarar, Selvarajah Thuseethan, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Marimuthu Palaniswami, Muhammad Ali Imran, Christopher Leckie, 2014, Pattern Recognit..

Online anomaly rate parameter tracking for anomaly detection in wireless sensor networks

Muhammad Ali Imran, Alexander Gluhak, Sutharshan Rajasegarar, 2012, 2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON).

CESVM: Centered Hyperellipsoidal Support Vector Machine Based Anomaly Detection

Marimuthu Palaniswami, Christopher Leckie, Sutharshan Rajasegarar, 2008, 2008 IEEE International Conference on Communications.

An efficient hyperellipsoidal clustering algorithm for resource-constrained environments

Christopher Leckie, Sutharshan Rajasegarar, Shanika Karunasekera, 2011, Pattern Recognit..

Anomaly detection in non-stationary data: Ensemble based self-adaptive OCSVM

Christopher Leckie, Sutharshan Rajasegarar, Shanika Karunasekera, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals

Sutharshan Rajasegarar, Chandan Karmakar, Tianrui Zong, 2020, IEEE Access.

A Statistical Moment Deviation Approach to Identify Outliers in Collaborative Spectrum Sensing for Cognitive Radio

Klaus Moessner, Sutharshan Rajasegarar, Asad Javied, 2012 .

Spatio-temporal modelling-based drift-aware wireless sensor networks

Marimuthu Palaniswami, Christopher Leckie, Subhash Challa, 2011, IET Wirel. Sens. Syst..

Acoustic and device feature fusion for load recognition

Muhammad Ali Imran, Ahmed Zoha, Alexander Gluhak, 2012, 2012 6th IEEE International Conference Intelligent Systems.

Elliptical anomalies in wireless sensor networks

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2009, TOSN.

Labelled data collection for anomaly detection in wireless sensor networks

Marimuthu Palaniswami, Sutharshan Rajasegarar, Shan Suthaharan, 2010, 2010 Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

An efficient approach to detecting concept-evolution in network data streams

Christopher Leckie, Sutharshan Rajasegarar, Sarah M. Erfani, 2011, 2011 Australasian Telecommunication Networks and Applications Conference (ATNAC).

Multiclass Anomaly Detector: the CS++ Support Vector Machine

Marimuthu Palaniswami, Sutharshan Rajasegarar, Alistair Shilton, 2020, J. Mach. Learn. Res..

Meta Learning Ensemble Technique for Diagnosis of Cardiac Autonomic Neuropathy Based on Heart Rate Variability Features

Jemal H. Abawajy, Herbert F. Jelinek, Sutharshan Rajasegarar, 2017 .

Geospatial Estimation-Based Auto Drift Correction in Wireless Sensor Networks

Marimuthu Palaniswami, Dheeraj Kumar, Sutharshan Rajasegarar, 2015, TOSN.

Detection of Anomalous Crowd Behaviour Using Hyperspherical Clustering

Marimuthu Palaniswami, Sutharshan Rajasegarar, Aravinda S. Rao, 2014, 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

Measures for clustering and anomaly detection in sets of higher dimensional ellipsoids

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Unsupervised Parameter Estimation for One-Class Support Vector Machines

Christopher Leckie, Sutharshan Rajasegarar, Shanika Karunasekera, 2016, PAKDD.

Efficient Unsupervised Parameter Estimation for One-Class Support Vector Machines

James C. Bezdek, Sutharshan Rajasegarar, Shanika Karunasekera, 2018, IEEE Transactions on Neural Networks and Learning Systems.

A Rapid Hybrid Clustering Algorithm for Large Volumes of High Dimensional Data

Marimuthu Palaniswami, James C. Bezdek, Dheeraj Kumar, 2019, IEEE Transactions on Knowledge and Data Engineering.

Sensor data boundary estimation for anomaly detection in wireless sensor networks

Christopher Leckie, Sutharshan Rajasegarar, Shanika Karunasekera, 2010, The 7th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2010).

Clustering ellipses for anomaly detection

Marimuthu Palaniswami, James M. Keller, Christopher Leckie, 2011, Pattern Recognit..

Profiling spatial and temporal behaviour in sensor networks: A case study in energy monitoring

Marimuthu Palaniswami, Muhammad Ali Imran, Christopher Leckie, 2014, 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

Deep Hybrid Spatiotemporal Networks for Continuous Pain Intensity Estimation

John Yearwood, Sutharshan Rajasegarar, Selvarajah Thuseethan, 2019, ICONIP.

Anomaly detection in wireless sensor networks

Marimuthu Palaniswami, Christopher Leckie, Sutharshan Rajasegarar, 2008, IEEE Wireless Communications.

Orness and Cardinality Indices for Averaging Inclusion-Exclusion Integrals

Sutharshan Rajasegarar, Simon James, Aoi Honda, 2017, MDAI.

The Role of Visual Assessment of Clusters for Big Data Analysis: From Real-World Internet of Things

Marimuthu Palaniswami, Sutharshan Rajasegarar, Aravinda S. Rao, 2020, IEEE Systems, Man, and Cybernetics Magazine.

Breast Cancer Recurrence Prediction Using Random Forest Model

Jemal H. Abawajy, Sutharshan Rajasegarar, Morshed U. Chowdhury, 2018, SCDM.

LGAttNet: Automatic micro-expression detection using dual-stream local and global attentions

John Yearwood, Sutharshan Rajasegarar, Min Xu, 2020, Knowl. Based Syst..

Smart car parking: Temporal clustering and anomaly detection in urban car parking

Marimuthu Palaniswami, Sutharshan Rajasegarar, Christopher Leckie, 2014, 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

Centered Hyperspherical and Hyperellipsoidal One-Class Support Vector Machines for Anomaly Detection in Sensor Networks

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2010, IEEE Transactions on Information Forensics and Security.

Detecting data anomalies in wireless sensor networks

Marimuthu Palaniswami, Christopher Leckie, Sutharshan Rajasegarar, 2010 .

Relationship Between Angiotensin Converting Enzyme Gene and Cardiac Autonomic Neuropathy Among Australian Population

Jemal H. Abawajy, Sutharshan Rajasegarar, Morshed U. Chowdhury, 2018, SCDM.

Adaptive Cluster Tendency Visualization and Anomaly Detection for Streaming Data

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2016, ACM Trans. Knowl. Discov. Data.

User Activity Pattern Analysis in Telecare Data

Sutharshan Rajasegarar, Maia Angelova, Helen Gibson, 2018, IEEE Access.

Fast and Scalable Big Data Trajectory Clustering for Understanding Urban Mobility

Marimuthu Palaniswami, Huayu Wu, Dheeraj Kumar, 2018, IEEE Transactions on Intelligent Transportation Systems.

Real-Time Urban Microclimate Analysis Using Internet of Things

Marimuthu Palaniswami, Sutharshan Rajasegarar, Aravinda S. Rao, 2018, IEEE Internet of Things Journal.

Distributed training of multiclass conic-segmentation support vector machines on communication constrained networks

Marimuthu Palaniswami, Alistair Shilton, Sutharshan Rajasegarar, 2010, 2010 Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

Automatic Sensor Drift Detection and Correction Using Spatial Kriging and Kalman Filtering

Marimuthu Palaniswami, Dheeraj Kumar, Sutharshan Rajasegarar, 2013, 2013 IEEE International Conference on Distributed Computing in Sensor Systems.

Investigation of Complexity and Regulatory Role of Physiological Activities During a Pacing Exercise

Sutharshan Rajasegarar, Maia Angelova, Sujan Rajbhandari, 2019, IEEE Access.

R1SVM: A Randomised Nonlinear Approach to Large-Scale Anomaly Detection

Christopher Leckie, Sutharshan Rajasegarar, Shanika Karunasekera, 2015, AAAI.

Anomalous Behavior Detection in Crowded Scenes Using Clustering and Spatio-Temporal Features

Marimuthu Palaniswami, Christopher Leckie, Sutharshan Rajasegarar, 2016, Intelligent Information Processing.

Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey

Muhammad Ali Imran, Ahmed Zoha, Alexander Gluhak, 2012, Sensors.

A Hybrid Approach to Clustering in Big Data

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2016, IEEE Transactions on Cybernetics.

Pattern based anomalous user detection in cognitive radio networks

Marimuthu Palaniswami, Christopher Leckie, Sutharshan Rajasegarar, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A visual-numeric approach to clustering and anomaly detection for trajectory data

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2017, The Visual Computer.

Deep Metric Learning Based Citrus Disease Classification With Sparse Data

John Yearwood, Sutharshan Rajasegarar, Yongqiang Zheng, 2020, IEEE Access.

Spatio-temporal estimation with Bayesian maximum entropy and compressive sensing in communication constrained networks

Marimuthu Palaniswami, Christopher Leckie, Sutharshan Rajasegarar, 2014, 2014 IEEE International Conference on Communications (ICC).

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning

Christopher Leckie, Sutharshan Rajasegarar, Shanika Karunasekera, 2016, Pattern Recognit..

IoT Insider Attack - Survey

Sutharshan Rajasegarar, Morshed U. Chowdhury, Robin Doss, 2020 .

Ensemble Fuzzy Clustering Using Cumulative Aggregation on Random Projections

Marimuthu Palaniswami, James C. Bezdek, Sutharshan Rajasegarar, 2018, IEEE Transactions on Fuzzy Systems.

Acoustic and device feature fusion for load recognition

Ahmed Zoha, Alexander Gluhak, Sutharshan Rajasegarar, 2012, 2012 6th IEEE International Conference Intelligent Systems.

Streaming analysis in wireless sensor networks

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2014, Wirel. Commun. Mob. Comput..

clusiVAT: A mixed visual/numerical clustering algorithm for big data

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2013, 2013 IEEE International Conference on Big Data.

VoterChoice: A ransomware detection honeypot with multiple voting framework

Sutharshan Rajasegarar, Frank Jiang, Leo Yu Zhang, 2020, Concurr. Comput. Pract. Exp..

Profiling Pedestrian Distribution and Anomaly Detection in a Dynamic Environment

Mahsa Salehi, Christopher Leckie, Sutharshan Rajasegarar, 2015, CIKM.

Bayesian maximum entropy and interacting multiple model based automatic sensor drift detection and correction in an IoT environment

Marimuthu Palaniswami, Dheeraj Kumar, Sutharshan Rajasegarar, 2018, 2018 IEEE 4th World Forum on Internet of Things (WF-IoT).

Crowd Activity Change Point Detection in Videos via Graph Stream Mining

Marimuthu Palaniswami, Christopher Leckie, Meng Yang, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Incremental Elliptical Boundary Estimation for Anomaly Detection in Wireless Sensor Networks

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2011, 2011 IEEE 11th International Conference on Data Mining.

High-Resolution Monitoring of Atmospheric Pollutants Using a System of Low-Cost Sensors

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2014, IEEE Transactions on Geoscience and Remote Sensing.

Non-invasive sensor based automated smoking activity detection

Sutharshan Rajasegarar, Xi Zheng, Jianchao Lu, 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

DP1SVM: A dynamic planar one-class support vector machine for Internet of Things environment

Marimuthu Palaniswami, Christopher Leckie, Alistair Shilton, 2015, 2015 International Conference on Recent Advances in Internet of Things (RIoT).

Node Re-Ordering as a Means of Anomaly Detection in Time-Evolving Graphs

James Bailey, Kotagiri Ramamohanarao, Christopher Leckie, 2016, ECML/PKDD.

Detection of Smoking Events from Confounding Activities of Daily Living

Sutharshan Rajasegarar, Xi Zheng, Jiaxing Wang, 2019, ACSW.

Improving load forecasting based on deep learning and K-shape clustering

Marimuthu Palaniswami, Christopher Leckie, Sutharshan Rajasegarar, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Breast cancer risk assessment prediction using an ensemble classifier

Jemal H. Abawajy, Sutharshan Rajasegarar, Morshed U. Chowdhury, 2017 .

Complex Emotion Profiling: An Incremental Active Learning Based Approach With Sparse Annotations

John Yearwood, Sutharshan Rajasegarar, Selvarajah Thuseethan, 2020, IEEE Access.

Detecting Micro-expression Intensity Changes from Videos Based on Hybrid Deep CNN

John Yearwood, Sutharshan Rajasegarar, Selvarajah Thuseethan, 2019, PAKDD.

Anomaly Detection in Environmental Monitoring Networks [Application Notes]

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2011, IEEE Computational Intelligence Magazine.

Cluster-Based Crowd Movement Behavior Detection

Marimuthu Palaniswami, Christopher Leckie, Meng Yang, 2018, 2018 Digital Image Computing: Techniques and Applications (DICTA).

Anomaly Detection in Wireless Sensor Networks in a Non-Stationary Environment

Muhammad Ali Imran, Alexander Gluhak, Sutharshan Rajasegarar, 2014, IEEE Communications Surveys & Tutorials.

Hyperspherical cluster based distributed anomaly detection in wireless sensor networks

Marimuthu Palaniswami, Christopher Leckie, Sutharshan Rajasegarar, 2014, J. Parallel Distributed Comput..

Fog-Empowered Anomaly Detection in IoT Using Hyperellipsoidal Clustering

Marimuthu Palaniswami, Lingjuan Lyu, Jiong Jin, 2017, IEEE Internet of Things Journal.

Quarter Sphere Based Distributed Anomaly Detection in Wireless Sensor Networks

Marimuthu Palaniswami, Christopher Leckie, James C. Bezdek, 2007, 2007 IEEE International Conference on Communications.

Parking availability prediction for sensor-enabled car parks in smart cities

Christopher Leckie, Sutharshan Rajasegarar, Yanxu Zheng, 2015, 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

A Novel Insider Attack and Machine Learning Based Detection for the Internet of Things

Sutharshan Rajasegarar, Sujan Chowdhury, Biplob Ray, 2021, ACM Trans. Internet Things.

Boosting Emotion Recognition in Context using Non-target Subject Information

John Yearwood, Sutharshan Rajasegarar, Selvarajah Thuseethan, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks

Sutharshan Rajasegarar, Alireza Tavakkoli, Sharif Amit Kamran, 2021, 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).

Deep Continual Learning for Emerging Emotion Recognition

John Yearwood, Sutharshan Rajasegarar, Selvarajah Thuseethan, 2022, IEEE Transactions on Multimedia.

Deep learning algorithms for cyber security applications: A survey

Sutharshan Rajasegarar, Nicholas Charles Patterson, Lei Pan, 2021, J. Comput. Secur..

A Scalable Framework for Clustering Vehicle Trajectories in a Dense Road Network

Marimuthu Palaniswami, Christopher Leckie, Dheeraj Kumar, 2015 .

Profiling Pedestrian Activity Patterns in a Dynamic Urban Environment

Christopher Leckie, Sutharshan Rajasegarar, Minh Tuan Doan, 2015 .

Sensor Network Implementation Challenges in The Great Barrier Reef Marine Environment

Marimuthu Palaniswami, Sutharshan Rajasegarar, Jayavardhana Gubbi, 2008 .