All papers authored by Sutharshan Rajasegarar
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Sergiy Shelyag ,
Sutharshan Rajasegarar ,
Dan Dwyer ,
Eun-Jin Kim ,
Maia Angelova
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Sergiy Shelyag ,
Sutharshan Rajasegarar ,
Daniel B. Dwyer ,
Eun-Jin Kim ,
Maia Angelova
Time-Series Analysis of Ball Carrier Open-Space in Association Football
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Sutharshan Rajasegarar ,
Lei Pan ,
Christopher Leckie ,
Sarah M. Erfani ,
Jeffrey Chan
LabelGen: An Anomaly Label Generative Framework for Enhanced Graph Anomaly Detection
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John Yearwood
Deep3DCANN: A Deep 3DCNN-ANN framework for spontaneous micro-expression recognition
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Adnan Anwar
Deakin microgrid digital twin and analysis of AI models for power generation prediction
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Meng Yang,
Sutharshan Rajasegarar
Deep learning-based real-time 3D human pose estimation
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Aravinda S. Rao,
Sutharshan Rajasegarar ,
Shucong Tian,
Zhengchun Zhou
Evolving graph-based video crowd anomaly detection
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Sutharshan Rajasegarar ,
Christopher Leckie ,
Sarah M. Erfani ,
Jeffrey Chan ,
Lei Pan
EnSpeciVAT: Enhanced SpecieVAT for Cluster Tendency Identification in Graphs
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Gang Liu,
Hong Xian Li,
Maia Angelova,
Gang Li
An Improved Visual Assessment with Data-Dependent Kernel for Stream Clustering
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Marimuthu Palaniswami,
Zhengchun Zhou
An efficient deep neural model for detecting crowd anomalies in videos
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Adnan Anwar,
Adam Fletcher
DμDT: the Deakin University Microgrid Digital Twin
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John Yearwood
EmoSeC: Emotion recognition from scene context
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Sutharshan Rajasegarar ,
John Yearwood
Deep Continual Learning for Emerging Emotion Recognition
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