Quarter Sphere Based Distributed Anomaly Detection in Wireless Sensor Networks. - Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami; James C. Bezdek (ICC, 2007)

Online drift correction in wireless sensor networks using spatio-temporal modeling. - Maen Takruri; Sutharshan Rajasegarar; Subhash Challa; Christopher Leckie; Marimuthu Palaniswami (FUSION, 2008)

CESVM: Centered Hyperellipsoidal Support Vector Machine Based Anomaly Detection. - Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami (ICC, 2008)

Anomaly detection in wireless sensor networks. - Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami (IEEE Wirel. Commun., 2008)

Elliptical anomalies in wireless sensor networks. - Sutharshan Rajasegarar; James C. Bezdek; Christopher Leckie; Marimuthu Palaniswami (ACM Trans. Sens. Networks, 2009)

Anomaly detection in wireless sensor networks. - Sutharshan Rajasegarar (2009)

Sensor data boundary estimation for anomaly detection in wireless sensor networks. - Shan Suthaharan; Christopher Leckie; Masud Moshtaghi; Shanika Karunasekera; Sutharshan Rajasegarar (MASS, 2010)

Centered hyperspherical and hyperellipsoidal one-class support vector machines for anomaly detection in sensor networks. - Sutharshan Rajasegarar; Christopher Leckie; James C. Bezdek; Marimuthu Palaniswami (IEEE Trans. Inf. Forensics Secur., 2010)

Incremental Elliptical Boundary Estimation for Anomaly Detection in Wireless Sensor Networks. - Masud Moshtaghi; Christopher Leckie; Shanika Karunasekera; James C. Bezdek; Sutharshan Rajasegarar; Marimuthu Palaniswami (ICDM, 2011)

An efficient approach to detecting concept-evolution in network data streams. - Sarah M. Erfani; Sutharshan Rajasegarar; Christopher Leckie (ATNAC, 2011)

Anomaly Detection in Environmental Monitoring Networks [Application Notes]. - James C. Bezdek; Sutharshan Rajasegarar; Masud Moshtaghi; Christopher Leckie; Marimuthu Palaniswami; Timothy C. Havens (IEEE Comput. Intell. Mag., 2011)

Spatio-temporal modelling-based drift-aware wireless sensor networks. - Maen Takruri; Sutharshan Rajasegarar; Subhash Challa; Christopher Leckie; Marimuthu Palaniswami (IET Wirel. Sens. Syst., 2011)

Clustering ellipses for anomaly detection. - Masud Moshtaghi; Timothy C. Havens; James C. Bezdek; Laurence Anthony F. Park; Christopher Leckie; Sutharshan Rajasegarar; James M. Keller; Marimuthu Palaniswami (Pattern Recognit., 2011)

An efficient hyperellipsoidal clustering algorithm for resource-constrained environments. - Masud Moshtaghi; Sutharshan Rajasegarar; Christopher Leckie; Shanika Karunasekera (Pattern Recognit., 2011)

Measures for clustering and anomaly detection in sets of higher dimensional ellipsoids. - Sutharshan Rajasegarar; James C. Bezdek; Masud Moshtaghi; Christopher Leckie; Timothy C. Havens; Marimuthu Palaniswami (IJCNN, 2012)

Acoustic and device feature fusion for load recognition. - Ahmed Zoha; Alexander Gluhak; Michele Nati; Muhammad Ali Imran 001; Sutharshan Rajasegarar (IEEE Conf. of Intelligent Systems, 2012)

Online anomaly rate parameter tracking for anomaly detection in wireless sensor networks. - Colin O'Reilly; Alexander Gluhak; Muhammad Ali Imran 001; Sutharshan Rajasegarar (SECON, 2012)

Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey. - Ahmed Zoha; Alexander Gluhak; Muhammad Ali Imran 001; Sutharshan Rajasegarar (Sensors, 2012)

clusiVAT: A mixed visual/numerical clustering algorithm for big data. - Dheeraj Kumar; Marimuthu Palaniswami; Sutharshan Rajasegarar; Christopher Leckie; James C. Bezdek; Timothy C. Havens (IEEE BigData, 2013)

Optimization of an energy harvesting buoy for coral reef monitoring. - Andrea Pirisi; Francesco Grimaccia; Marco Mussetta; Riccardo Enrico Zich; Ron Johnstone; Marimuthu Palaniswami; Sutharshan Rajasegarar (IEEE Congress on Evolutionary Computation, 2013)

Automatic Sensor Drift Detection and Correction Using Spatial Kriging and Kalman Filtering. - Dheeraj Kumar; Sutharshan Rajasegarar; Marimuthu Palaniswami (DCOSS, 2013)

Combined multiclass classification and anomaly detection for large-scale Wireless Sensor Networks. - Alistair Shilton; Sutharshan Rajasegarar; Marimuthu Palaniswami (ISSNIP, 2013)

Detection of Anomalous Crowd Behaviour Using Hyperspherical Clustering. - Aravinda S. Rao; Jayavardhana Gubbi; Sutharshan Rajasegarar; Slaven Marusic; Marimuthu Palaniswami (DICTA, 2014)

Spatio-temporal estimation with Bayesian maximum entropy and compressive sensing in communication constrained networks. - Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami (ICC, 2014)

High resolution spatio-temporal monitoring of air pollutants using wireless sensor networks. - Sutharshan Rajasegarar; Peng Zhang; Yang Zhou; Shanika Karunasekera; Christopher Leckie; Marimuthu Palaniswami (ISSNIP, 2014)

Profiling spatial and temporal behaviour in sensor networks: A case study in energy monitoring. - Lida Rashidi; Sutharshan Rajasegarar; Christopher Leckie; Michele Nati; Alexander Gluhak; Muhammad Ali Imran 001; Marimuthu Palaniswami (ISSNIP, 2014)

Smart car parking: Temporal clustering and anomaly detection in urban car parking. - Yanxu Zheng; Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami (ISSNIP, 2014)

An adaptive elliptical anomaly detection model for wireless sensor networks. - Masud Moshtaghi; Christopher Leckie; Shanika Karunasekera; Sutharshan Rajasegarar (Comput. Networks, 2014)

Anomaly Detection in Wireless Sensor Networks in a Non-Stationary Environment. - Colin O'Reilly; Alexander Gluhak; Muhammad Ali Imran 001; Sutharshan Rajasegarar (IEEE Commun. Surv. Tutorials, 2014)

Hyperspherical cluster based distributed anomaly detection in wireless sensor networks. - Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami (J. Parallel Distributed Comput., 2014)

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks. - Sutharshan Rajasegarar; Alexander Gluhak; Muhammad Ali Imran 001; Michele Nati; Masud Moshtaghi; Christopher Leckie; Marimuthu Palaniswami (Pattern Recognit., 2014)

High-Resolution Monitoring of Atmospheric Pollutants Using a System of Low-Cost Sensors. - Sutharshan Rajasegarar; Timothy C. Havens; Shanika Karunasekera; Christopher Leckie; James C. Bezdek; Milan Jamriska; Ajith Gunatilaka; Alex Skvortsov; Marimuthu Palaniswami (IEEE Trans. Geosci. Remote. Sens., 2014)

Streaming analysis in wireless sensor networks. - Masud Moshtaghi; James C. Bezdek; Timothy C. Havens; Christopher Leckie; Shanika Karunasekera; Sutharshan Rajasegarar; Marimuthu Palaniswami (Wirel. Commun. Mob. Comput., 2014)

R1SVM: A Randomised Nonlinear Approach to Large-Scale Anomaly Detection. - Sarah M. Erfani; Mahsa Baktashmotlagh; Sutharshan Rajasegarar; Shanika Karunasekera; Christopher Leckie (AAAI, 2015)

Profiling Pedestrian Distribution and Anomaly Detection in a Dynamic Environment. - Minh Tuan Doan; Sutharshan Rajasegarar; Mahsa Salehi; Masud Moshtaghi; Christopher Leckie (CIKM, 2015)

Pattern based anomalous user detection in cognitive radio networks. - Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami (ICASSP, 2015)

Parking availability prediction for sensor-enabled car parks in smart cities. - Yanxu Zheng; Sutharshan Rajasegarar; Christopher Leckie (ISSNIP, 2015)

An Embedding Scheme for Detecting Anomalous Block Structured Graphs. - Lida Rashidi; Sutharshan Rajasegarar; Christopher Leckie (PAKDD (2), 2015)

DP1SVM: A dynamic planar one-class support vector machine for Internet of Things environment. - Alistair Shilton; Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami (RIoT, 2015)

Geospatial Estimation-Based Auto Drift Correction in Wireless Sensor Networks. - Dheeraj Kumar; Sutharshan Rajasegarar; Marimuthu Palaniswami (ACM Trans. Sens. Networks, 2015)

Anomalous Behavior Detection in Crowded Scenes Using Clustering and Spatio-Temporal Features. - Meng Yang 007; Sutharshan Rajasegarar; Aravinda S. Rao; Christopher Leckie; Marimuthu Palaniswami (IIP, 2016)

Anomaly detection in non-stationary data: Ensemble based self-adaptive OCSVM. - Zahra Ghafoori; Sarah M. Erfani; Sutharshan Rajasegarar; Shanika Karunasekera; Christopher A. Leckie (IJCNN, 2016)

Unsupervised Parameter Estimation for One-Class Support Vector Machines. - Zahra Ghafoori; Sutharshan Rajasegarar; Sarah M. Erfani; Shanika Karunasekera; Christopher A. Leckie (PAKDD (2), 2016)

Pedestrian behaviour analysis using the microsoft kinect. - Junying Chen; Sutharshan Rajasegarar; Christopher Leckie; André F. Gygax (PerCom Workshops, 2016)

Node Re-Ordering as a Means of Anomaly Detection in Time-Evolving Graphs. - Lida Rashidi; Andrey Kan; James Bailey 001; Jeffrey Chan; Christopher Leckie; Wei Liu 007; Sutharshan Rajasegarar; Kotagiri Ramamohanarao (ECML/PKDD (2), 2016)

R1STM: One-class Support Tensor Machine with Randomised Kernel. - Sarah M. Erfani; Mahsa Baktashmotlagh; Sutharshan Rajasegarar; Vinh Nguyen; Christopher Leckie; James Bailey 001; Kotagiri Ramamohanarao (SDM, 2016)

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning. - Sarah M. Erfani; Sutharshan Rajasegarar; Shanika Karunasekera; Christopher Leckie (Pattern Recognit., 2016)

A Hybrid Approach to Clustering in Big Data. - Dheeraj Kumar; James C. Bezdek; Marimuthu Palaniswami; Sutharshan Rajasegarar; Christopher Leckie; Timothy Craig Havens (IEEE Trans. Cybern., 2016)

Adaptive Cluster Tendency Visualization and Anomaly Detection for Streaming Data. - Dheeraj Kumar; James C. Bezdek; Sutharshan Rajasegarar; Marimuthu Palaniswami; Christopher Leckie; Jeffrey Chan; Jayavardhana Gubbi (ACM Trans. Knowl. Discov. Data, 2016)

Distributed Detection of Zero-Day Network Traffic Flows. - Yuantian Miao; Lei Pan 002; Sutharshan Rajasegarar; Jun Zhang 010; Christopher Leckie; Yang Xiang 001 (AusDM, 2017)

Non-invasive sensor based automated smoking activity detection. - Babin Bhandari; Jianchao Lu; Xi Zheng 001; Sutharshan Rajasegarar; Chandan K. Karmakar (EMBC, 2017)

Improving load forecasting based on deep learning and K-shape clustering. - Fateme Fahiman; Sarah M. Erfani; Sutharshan Rajasegarar; Marimuthu Palaniswami; Christopher Leckie (IJCNN, 2017)

Orness and Cardinality Indices for Averaging Inclusion-Exclusion Integrals. - Aoi Honda; Simon James; Sutharshan Rajasegarar (MDAI, 2017)

Clustering Aided Support Vector Machines. - Goce Ristanoski; Rahul Soni; Sutharshan Rajasegarar; James Bailey 001; Christopher Leckie (MLDM, 2017)

Fog-Empowered Anomaly Detection in IoT Using Hyperellipsoidal Clustering. - Lingjuan Lyu; Jiong Jin; Sutharshan Rajasegarar; Xuanli He; Marimuthu Palaniswami (IEEE Internet Things J., 2017)

Maximum Entropy-Based Auto Drift Correction Using High- and Low-Precision Sensors. - Punit Rathore; Dheeraj Kumar; Sutharshan Rajasegarar; Marimuthu Palaniswami (ACM Trans. Sens. Networks, 2017)

A visual-numeric approach to clustering and anomaly detection for trajectory data. - Dheeraj Kumar; James C. Bezdek; Sutharshan Rajasegarar; Christopher Leckie; Marimuthu Palaniswami (Vis. Comput., 2017)

Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data. - Minh Tuan Doan; Jianzhong Qi 001; Sutharshan Rajasegarar; Christopher Leckie (IEEE BigData, 2018)

Crowd Activity Change Point Detection in Videos via Graph Stream Mining. - Meng Yang 007; Lida Rashidi; Sutharshan Rajasegarar; Christopher Leckie; Aravinda S. Rao; Marimuthu Palaniswami (CVPR Workshops, 2018)

Cluster-Based Crowd Movement Behavior Detection. - Meng Yang 007; Lida Rashidi; Aravinda S. Rao; Sutharshan Rajasegarar; Mohadeseh Ganji; Marimuthu Palaniswami; Christopher Leckie (DICTA, 2018)

Approximate Cluster Heat Maps of Large High-Dimensional Data. - Punit Rathore; James C. Bezdek; Dheeraj Kumar; Sutharshan Rajasegarar; Marimuthu Palaniswami (ICPR, 2018)

Graph Stream Mining Based Anomalous Event Analysis. - Meng Yang 007; Lida Rashidi; Sutharshan Rajasegarar; Christopher Leckie (PRICAI (1), 2018)

Relationship Between Angiotensin Converting Enzyme Gene and Cardiac Autonomic Neuropathy Among Australian Population. - Ahmad Shaker Abdalrada; Jemal H. Abawajy; Morshed U. Chowdhury; Sutharshan Rajasegarar; Tahsien Al-Quraishi; Herbert F. Jelinek (SCDM, 2018)

Breast Cancer Recurrence Prediction Using Random Forest Model. - Tahsien Al-Quraishi; Jemal H. Abawajy; Morshed U. Chowdhury; Sutharshan Rajasegarar; Ahmad Shaker Abdalrada (SCDM, 2018)

Bayesian maximum entropy and interacting multiple model based automatic sensor drift detection and correction in an IoT environment. - Punit Rathore; Dheeraj Kumar; Sutharshan Rajasegarar; Marimuthu Palaniswami (WF-IoT, 2018)

User Activity Pattern Analysis in Telecare Data. - Maia Angelova; Jeremy Ellman; Helen Gibson; Paul Oman 001; Sutharshan Rajasegarar; Ye Zhu 002 (IEEE Access, 2018)

Real-Time Urban Microclimate Analysis Using Internet of Things. - Punit Rathore; Aravinda S. Rao; Sutharshan Rajasegarar; Elena Vanz; Jayavardhana Gubbi; Marimuthu Palaniswami (IEEE Internet Things J., 2018)

Ensemble Fuzzy Clustering Using Cumulative Aggregation on Random Projections. - Punit Rathore; James C. Bezdek; Sarah M. Erfani; Sutharshan Rajasegarar; Marimuthu Palaniswami (IEEE Trans. Fuzzy Syst., 2018)

Fast and Scalable Big Data Trajectory Clustering for Understanding Urban Mobility. - Dheeraj Kumar; Huayu Wu 001; Sutharshan Rajasegarar; Christopher Leckie; Shonali Krishnaswamy; Marimuthu Palaniswami (IEEE Trans. Intell. Transp. Syst., 2018)

Efficient Unsupervised Parameter Estimation for One-Class Support Vector Machines. - Zahra Ghafoori; Sarah M. Erfani; Sutharshan Rajasegarar; James C. Bezdek; Shanika Karunasekera; Christopher Leckie (IEEE Trans. Neural Networks Learn. Syst., 2018)

Detection of Smoking Events from Confounding Activities of Daily Living. - Jianchao Lu; Jiaxing Wang 002; Xi Zheng 001; Chandan K. Karmakar; Sutharshan Rajasegarar (ACSW, 2019)

Insider Attacks on Zigbee Based IoT Networks by Exploiting AT Commands. - Waqas Ahmad Piracha; Morshed U. Chowdhury; Biplob Ray; Sutharshan Rajasegarar; Robin Doss (ATIS, 2019)

Deep Hybrid Spatiotemporal Networks for Continuous Pain Intensity Estimation. - Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (ICONIP (3), 2019)

Emotion Intensity Estimation from Video Frames using Deep Hybrid Convolutional Neural Networks. - Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (IJCNN, 2019)

Deep Learning and One-class SVM based Anomalous Crowd Detection. - Meng Yang 007; Sutharshan Rajasegarar; Sarah M. Erfani; Christopher Leckie (IJCNN, 2019)

Detecting Micro-expression Intensity Changes from Videos Based on Hybrid Deep CNN. - Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (PAKDD (3), 2019)

IoT Insider Attack - Survey. - Morshed U. Chowdhury; Robin Doss; Biplob Ray; Sutharshan Rajasegarar; Sujan Chowdhury (SGIoT, 2019)

Investigation of Complexity and Regulatory Role of Physiological Activities During a Pacing Exercise. - Maia Angelova; Sergiy Shelyag; Sutharshan Rajasegarar; Dineshen Chuckravanen; Sujan Rajbhandari; Paul B. Gastin; Alan St Clair Gibson (IEEE Access, 2019)

A Scalable Framework for Trajectory Prediction. - Punit Rathore; Dheeraj Kumar; Sutharshan Rajasegarar; Marimuthu Palaniswami; James C. Bezdek (IEEE Trans. Intell. Transp. Syst., 2019)

A Rapid Hybrid Clustering Algorithm for Large Volumes of High Dimensional Data. - Punit Rathore; Dheeraj Kumar; James C. Bezdek; Sutharshan Rajasegarar; Marimuthu Palaniswami (IEEE Trans. Knowl. Data Eng., 2019)

Multi-Attention 3D Residual Neural Network for Origin-Destination Crowd Flow Prediction. - Jiaman Ma; Jeffrey Chan; Sutharshan Rajasegarar; Goce Ristanoski; Christopher Leckie (ICDM, 2020)

Graph Deep Learning Based Anomaly Detection in Ethereum Blockchain Network. - Vatsal Patel; Lei Pan 002; Sutharshan Rajasegarar (NSS, 2020)

Multimodal Deep Learning Framework for Sentiment Analysis from Text-Image Web Data. - Selvarajah Thuseethan; Sivasubramaniam Janarthan; Sutharshan Rajasegarar; Priya Kumari; John Yearwood (WI/IAT, 2020)

Deep Metric Learning Based Citrus Disease Classification With Sparse Data. - Sivasubramaniam Janarthan; Selvarajah Thuseethan; Sutharshan Rajasegarar; Qiang Lyu; Yongqiang Zheng; John Yearwood (IEEE Access, 2020)

Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals. - Iynkaran Natgunanathan; Chandan K. Karmakar; Sutharshan Rajasegarar; Tianrui Zong; Ahsan Habib 003 (IEEE Access, 2020)

Complex Emotion Profiling: An Incremental Active Learning Based Approach With Sparse Annotations. - Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (IEEE Access, 2020)

VoterChoice: A ransomware detection honeypot with multiple voting framework. - Chee Keong Ng; Sutharshan Rajasegarar; Lei Pan 002; Frank Jiang 001; Leo Yu Zhang (Concurr. Comput. Pract. Exp., 2020)

Multiclass Anomaly Detector: the CS++ Support Vector Machine. - Alistair Shilton; Sutharshan Rajasegarar; Marimuthu Palaniswami (J. Mach. Learn. Res., 2020)

Gathering Intelligence on Student Information Behavior Using Data Mining. - Lei Pan 002; Nicholas Charles Patterson; Sophie McKenzie; Surtharshan Rajasegarar; Guy Wood-Bradley; Justin T. Rough; Wei Luo 001; Elicia Lanham; Jo Coldwell-Neilson (Libr. Trends, 2020)

Identification of Stock Market Manipulation with Deep Learning. - Jillian Tallboys; Ye Zhu 002; Sutharshan Rajasegarar (ADMA, 2021)

ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks. - Khondker Fariha Hossain; Sharif Amit Kamran; Alireza Tavakkoli; Lei Pan 002; Xingjun Ma; Sutharshan Rajasegarar; Chandan Karmaker (ICMLA, 2021)

Boosting Emotion Recognition in Context using Non-target Subject Information. - Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (IJCNN, 2021)

ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks. - Khondker Fariha Hossain; Sharif Amit Kamran; Alireza Tavakkoli; Lei Pan 002; Daniel Ma; Sutharshan Rajasegarar; Chandan Karmaker (CoRR, 2021)

Deep learning algorithms for cyber security applications: A survey. - Guangjun Li; Preetpal Sharma; Lei Pan 002; Sutharshan Rajasegarar; Chandan K. Karmakar; Nicholas Charles Patterson (J. Comput. Secur., 2021)

LGAttNet: Automatic micro-expression detection using dual-stream local and global attentions. - Madhumita A. Takalkar; Selvarajah Thuseethan; Sutharshan Rajasegarar; Zenon Chaczko; Min Xu 001; John Yearwood (Knowl. Based Syst., 2021)

Visual Structural Assessment and Anomaly Detection for High-Velocity Data Streams. - Punit Rathore; Dheeraj Kumar; James C. Bezdek; Sutharshan Rajasegarar; Marimuthu Palaniswami (IEEE Trans. Cybern., 2021)

A Novel Insider Attack and Machine Learning Based Detection for the Internet of Things. - Morshed U. Chowdhury; Biplob Ray; Sujan Chowdhury; Sutharshan Rajasegarar (ACM Trans. Internet Things, 2021)

Cyber Attack Detection in IoT Networks with Small Samples: Implementation And Analysis. - Venkata Abhishek Kanthuru; Sutharshan Rajasegarar; Punit Rathore; Robin Ram Mohan Doss; Lei Pan 002; Biplob Ray; Morshed Chowdhury; Chandrasekaran Srimathi; M. A. Saleem Durai (ADMA (1), 2022)

EvAnGCN: Evolving Graph Deep Neural Network Based Anomaly Detection in Blockchain. - Vatsal Patel; Sutharshan Rajasegarar; Lei Pan 002; Jiajun Liu; Liming Zhu 001 (ADMA (1), 2022)

Machine Learning Aided Minimal Sensor based Hand Gesture Character Recognition. - Noorain Zaidi; Priya Kumari; Sutharshan Rajasegarar; Chandan K. Karmakar (DSAA, 2022)

Double Attention-Based Lightweight Network for Plant Pest Recognition. - Sivasubramaniam Janarthan; Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (ICONIP (6), 2022)

Exploiting Redundancy in Network Flow Information for Efficient Security Attack Detection. - Siqi Xia; Sutharshan Rajasegarar; Christopher Leckie; Sarah M. Erfani; Jeffrey Chan (NSS, 2022)

P2OP - Plant Pathology on Palms: A deep learning-based mobile solution for in-field plant disease detection. - Sivasubramaniam Janarthan; Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (Comput. Electron. Agric., 2022)

Multi-attention graph neural networks for city-wide bus travel time estimation using limited data. - Jiaman Ma; Jeffrey Chan; Sutharshan Rajasegarar; Christopher Leckie (Expert Syst. Appl., 2022)

EmoSeC: Emotion recognition from scene context. - Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (Neurocomputing, 2022)

Deep Continual Learning for Emerging Emotion Recognition. - Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (IEEE Trans. Multim., 2022)

EnSpeciVAT: Enhanced SpecieVAT for Cluster Tendency Identification in Graphs. - Siqi Xia; Sutharshan Rajasegarar; Christopher Leckie; Sarah M. Erfani; Jeffrey Chan; Lei Pan 002 (ADMA (3), 2023)

Quantum Autoencoder Frameworks for Network Anomaly Detection. - Moe Hdaib; Sutharshan Rajasegarar; Lei Pan 002 (ICONIP (5), 2023)

An Improved Visual Assessment with Data-Dependent Kernel for Stream Clustering. - Baojie Zhang; Yang Cao 019; Ye Zhu 002; Sutharshan Rajasegarar; Gang Liu 021; Hong Xian Li; Maia Angelova; Gang Li 009 (PAKDD (1), 2023)

It's PageRank All The Way Down: Simplifying Deep Graph Networks. - Dominic Jack; Sarah M. Erfani; Jeffrey Chan; Sutharshan Rajasegarar; Christopher Leckie (SDM, 2023)

Deep learning-based real-time 3D human pose estimation. - Xiaoyan Zhang; Zhengchun Zhou; Ying Han; Hua Meng 001; Meng Yang 007; Sutharshan Rajasegarar (Eng. Appl. Artif. Intell., 2023)

An efficient deep neural model for detecting crowd anomalies in videos. - Meng Yang 007; Shucong Tian; Aravinda S. Rao; Sutharshan Rajasegarar; Marimuthu Palaniswami; Zhengchun Zhou (Appl. Intell., 2023)

Deep3DCANN: A Deep 3DCNN-ANN framework for spontaneous micro-expression recognition. - Selvarajah Thuseethan; Sutharshan Rajasegarar; John Yearwood (Inf. Sci., 2023)

ConDGAD: Multi-augmentation Contrastive Learning for Dynamic Graph Anomaly Detection. - Siqi Xia; Sutharshan Rajasegarar; Lei Pan 002; Christopher Leckie; Sarah M. Erfani; Jeffrey Chan (ICPR (25), 2024)

Time-Series Analysis of Ball Carrier Open-Space in Association Football. - Ishara Bandara; Sergiy Shelyag; Sutharshan Rajasegarar; Daniel B. Dwyer; Eun-Jin Kim; Maia Angelova (ISACE, 2024)

Gold Price Forecasting in Uncertain Times: Integrating Sentiment Analysis and External Indices. - Dat Le; Sutharshan Rajasegarar; Wei Luo 001; Thanh Thi Nguyen; Maia Angelova (ISCMI, 2024)

Winning With Chaos in Association Football: Spatiotemporal Event Distribution Randomness Metric for Team Performance Evaluation. - Ishara Bandara; Sergiy Shelyag; Sutharshan Rajasegarar; Dan Dwyer; Eun-Jin Kim; Maia Angelova (IEEE Access, 2024)

LabelGen: An Anomaly Label Generative Framework for Enhanced Graph Anomaly Detection. - Siqi Xia; Sutharshan Rajasegarar; Lei Pan 002; Christopher Leckie; Sarah M. Erfani; Jeffrey Chan (IEEE Access, 2024)

Robust Zero Trust Architecture: Joint Blockchain based Federated learning and Anomaly Detection based Framework. - Shiva Raj Pokhrel; Luxing Yang; Sutharshan Rajasegarar; Gang Li 009 (CoRR, 2024)

A sequential multi-agent reinforcement learning framework for different action spaces. - Shucong Tian; Meng Yang 007; Rongling Xiong; Xingxing He; Sutharshan Rajasegarar (Expert Syst. Appl., 2024)

Evolving graph-based video crowd anomaly detection. - Meng Yang 007; Yanghe Feng; Aravinda S. Rao; Sutharshan Rajasegarar; Shucong Tian; Zhengchun Zhou (Vis. Comput., 2024)

Quantum deep learning-based anomaly detection for enhanced network security. - Moe Hdaib; Sutharshan Rajasegarar; Lei Pan 002 (Quantum Mach. Intell., 2024)

Kernel-based iVAT with adaptive cluster extraction. - Baojie Zhang; Ye Zhu 002; Yang Cao 019; Sutharshan Rajasegarar; Gang Li 009; Gang Liu 021 (Knowl. Inf. Syst., 2024)

Double-layer data-hiding mechanism for ECG signals. - Iynkaran Natgunanathan; Chandan K. Karmakar; Sutharshan Rajasegarar; Tianrui Zong (EURASIP J. Adv. Signal Process., 2024)

Large Language Model and Variational Autoencoder Based Deep Neural Framework for Cyber Attack Detection. - Zhi Liu; Jyotheesh Gaddam; Shuo Huang; Ishara Bandara; Ming Liu 028; Sutharshan Rajasegarar; Muneeb Ul Hassan 001; Luxing Yang; Gang Li 009; Maia Angelova (PAKDD (4), 2025)

Background-Masked Lightweight Approach for Pear Leaf Disease Recognition. - Romiyal George; Selvarajah Thuseethan; Roshan G. Ragel; Sutharshan Rajasegarar; Mamoun Alazab; Hamish Campbell; John Yearwood (IEEE Access, 2025)

Time-Series Analysis of Ball Carrier Open-Space (BCOS) in Association Football. - Ishara Bandara; Sergiy Shelyag; Sutharshan Rajasegarar; Daniel B. Dwyer; Eunjin Kim; Maia Angelova (SN Comput. Sci., 2025)