Outputs (93)

Unraveling the brain dynamics of Depersonalization-Derealization Disorder: a dynamic functional network connectivity analysis (2024)
Journal Article
Zheng, S., Zhang, F. X., Shum, H. P. H., Zhang, H., Song, N., Song, M., & Jia, H. (2024). Unraveling the brain dynamics of Depersonalization-Derealization Disorder: a dynamic functional network connectivity analysis. BMC Psychiatry, 24, Article 685. https://doi.org/10.1186/s12888-024-06096-1

Background: Depersonalization-Derealization Disorder (DPD), a prevalent psychiatric disorder, fundamentally disrupts self-consciousness and could significantly impact the quality of life of those affected. While existing research has provided foundat... Read More about Unraveling the brain dynamics of Depersonalization-Derealization Disorder: a dynamic functional network connectivity analysis.

Advancing healthcare practice and education via data sharing: demonstrating the utility of open data by training an artificial intelligence model to assess cardiopulmonary resuscitation skills. (2024)
Journal Article
Constable, M. D., Zhang, F. X., Conner, T., Monk, D., Rajsic, J., Ford, C., Park, L. J., Platt, A., Porteous, D., Grierson, L., & Shum, H. P. H. (online). Advancing healthcare practice and education via data sharing: demonstrating the utility of open data by training an artificial intelligence model to assess cardiopulmonary resuscitation skills. Advances in Health Sciences Education, https://doi.org/10.1007/s10459-024-10369-5

Health professional education stands to gain substantially from collective efforts toward building video databases of skill performances in both real and simulated settings. An accessible resource of videos that demonstrate an array of performances –... Read More about Advancing healthcare practice and education via data sharing: demonstrating the utility of open data by training an artificial intelligence model to assess cardiopulmonary resuscitation skills..

One-Index Vector Quantization Based Adversarial Attack on Image Classification (2024)
Journal Article
Fan, H., Qin, X., Chen, S., Shum, H. P. H., & Li, M. (2024). One-Index Vector Quantization Based Adversarial Attack on Image Classification. Pattern Recognition Letters, 186, 47-56. https://doi.org/10.1016/j.patrec.2024.09.001

To improve storage and transmission, images are generally compressed. Vector quantization (VQ) is a popular compression method as it has a high compression ratio that suppresses other compression techniques. Despite this, existing adversarial attack... Read More about One-Index Vector Quantization Based Adversarial Attack on Image Classification.

ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification (2024)
Book Chapter
Vijendran, M., Li, F. W. B., Deng, J., & Shum, H. P. H. (in press). ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification. In CCIS '24: Communications in Computer and Information Science. Springer

Geometric Features Enhanced Human-Object Interaction Detection (2024)
Journal Article
Zhu, M., Ho, E. S. L., Chen, S., Yang, L., & Shum, H. P. H. (2024). Geometric Features Enhanced Human-Object Interaction Detection. IEEE Transactions on Instrumentation and Measurement, 73, Article 5026014. https://doi.org/10.1109/TIM.2024.3427800

Cameras are essential vision instruments to capture images for pattern detection and measurement. Human–object interaction (HOI) detection is one of the most popular pattern detection approaches for captured human-centric visual scenes. Recently, Tra... Read More about Geometric Features Enhanced Human-Object Interaction Detection.

HINT: High-quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention (2024)
Journal Article
Chen, S., Atapour-Abarghouei, A., & Shum, H. P. H. (2024). HINT: High-quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention. IEEE Transactions on Multimedia, 26, 7649-7660. https://doi.org/10.1109/TMM.2024.3369897

Existing image inpainting methods leverage convolution-based downsampling approaches to reduce spatial dimensions. This may result in information loss from corrupted images where the available information is inherently sparse, especially for the scen... Read More about HINT: High-quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention.

Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review (2024)
Journal Article
Constable, M. D., Shum, H. P. H., & Clark, S. (2024). Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review. Journal of Cardiothoracic Surgery, 19(1), Article 94. https://doi.org/10.1186/s13019-024-02558-5

When technical requirements are high, and patient outcomes are critical, opportunities for monitoring and improving surgical skills via objective motion analysis feedback may be particularly beneficial. This narrative review synthesises work on techn... Read More about Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review.

Pose-based tremor type and level analysis for Parkinson’s disease from video (2024)
Journal Article
Zhang, H., Ho, E. S. L., Zhang, X., Del Din, S., & Shum, H. P. H. (2024). Pose-based tremor type and level analysis for Parkinson’s disease from video. International Journal of Computer Assisted Radiology and Surgery, 19(5), 831-840. https://doi.org/10.1007/s11548-023-03052-4

Current methods for diagnosis of PD rely on clinical examination. The accuracy of diagnosis ranges between 73 and 84%, and is influenced by the experience of the clinical assessor. Hence, an automatic, effective and interpretable supporting system fo... Read More about Pose-based tremor type and level analysis for Parkinson’s disease from video.

Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles (2023)
Journal Article
Crosato, L., Tian, K., Shum, H. P., Ho, E. S., Wang, Y., & Wei, C. (2023). Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles. Advanced Intelligent Systems, 6(3), Article 2300575. https://doi.org/10.1002/aisy.202300575

Interaction‐aware autonomous driving (IAAD) is a rapidly growing field of research that focuses on the development of autonomous vehicles (AVs) that are capable of interacting safely and efficiently with human road users. This is a challenging task,... Read More about Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles.

Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising (2023)
Journal Article
Zhou, K., Shum, H. P., Li, F. W., & Liang, X. (2023). Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising. IEEE Transactions on Visualization and Computer Graphics, https://doi.org/10.1109/TVCG.2023.3337868

In many human-computer interaction applications, fast and accurate hand tracking is necessary for an immersive experience. However, raw hand motion data can be flawed due to issues such as joint occlusions and high-frequency noise, hindering the inte... Read More about Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising.