All Outputs (5)

A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction (2022)
Journal Article
Zhu, M., Men, Q., Ho, E. S., Leung, H., & Shum, H. P. (2022). A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction. Journal of Medical Systems, 46(11), Article 76. https://doi.org/10.1007/s10916-022-01857-5

Musculoskeletal and neurological disorders are the most common causes of walking problems among older people, and they often lead to diminished quality of life. Analyzing walking motion data manually requires trained professionals and the evaluations... Read More about A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction.

CP-AGCN: Pytorch-based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy (2022)
Journal Article
Zhang, H., Ho, E. S., & Shum, H. P. (2022). CP-AGCN: Pytorch-based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy. Software impacts, 14, Article 100419. https://doi.org/10.1016/j.simpa.2022.100419

Early prediction is clinically considered one of the essential parts of cerebral palsy (CP) treatment. We propose to implement a low-cost and interpretable classification system for supporting CP prediction based on General Movement Assessment (GMA).... Read More about CP-AGCN: Pytorch-based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy.

Interaction-aware Decision-making for Automated Vehicles using Social Value Orientation (2022)
Journal Article
Crosato, L., Shum, H. P., Ho, E. S., & Wei, C. (2023). Interaction-aware Decision-making for Automated Vehicles using Social Value Orientation. IEEE Transactions on Intelligent Vehicles, 8(2), 1339-1349. https://doi.org/10.1109/tiv.2022.3189836

Motion control algorithms in the presence of pedestrians are critical for the development of safe and reliable Autonomous Vehicles (AVs). Traditional motion control algorithms rely on manually designed decision-making policies which neglect the mutua... Read More about Interaction-aware Decision-making for Automated Vehicles using Social Value Orientation.

Formation Control for UAVs Using a Flux Guided Approach (2022)
Journal Article
Hartley, J., Shum, H. P., Ho, E. S., Wang, H., & Ramamoorthyd, S. (2022). Formation Control for UAVs Using a Flux Guided Approach. Expert Systems with Applications, 205, Article 117665. https://doi.org/10.1016/j.eswa.2022.117665

Existing studies on formation control for unmanned aerial vehicles (UAV) have not considered encircling targets where an optimum coverage of the target is required at all times. Such coverage plays a critical role in many real-world applications such... Read More about Formation Control for UAVs Using a Flux Guided Approach.

RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis (2022)
Journal Article
Organisciak, D., Shum, H. P., Nwoye, E., & Woo, W. L. (2022). RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis. Expert Systems with Applications, 201, Article 117158. https://doi.org/10.1016/j.eswa.2022.117158

Schizophrenia is a severe mental health condition that requires a long and complicated diagnostic process. However, early diagnosis is vital to control symptoms. Deep learning has recently become a popular way to analyse and interpret medical data. P... Read More about RobIn: A Robust Interpretable Deep Network for Schizophrenia Diagnosis.