Outputs (98)

Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach (2023)
Journal Article
Albusac, J., Herrera, V., Schez-Sobrino, S., Grande, R., Vallejo, D., & Monekosso, D. (2024). Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach. Multimedia Tools and Applications, 83, 60537-60563. https://doi.org/10.1007/s11042-023-17892-4

The integration of technology in healthcare has revolutionized physical rehabilitation of patients affected by neurological conditions, such as spinal cord injuries and strokes. However, a significant gap remains in addressing the needs of the visual... Read More about Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach.

Trustworthy IAP: An Intelligent Applications Profiler to Investigate Vulnerabilities of Consumer Electronic Devices (2023)
Journal Article
Su, J., Hong, Z., Ye, L., Liu, T., Liang, S., Ji, S., …Wen, Z. (2023). Trustworthy IAP: An Intelligent Applications Profiler to Investigate Vulnerabilities of Consumer Electronic Devices. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/tce.2023.3347651

As a typical representative of the Internet of Energy (IoE) intelligent era, consumer electronic (CE) devices continue to evolve at a remarkable pace. Computers, as typical and essential CE devices, have been instrumental in enhancing efficiency, com... Read More about Trustworthy IAP: An Intelligent Applications Profiler to Investigate Vulnerabilities of Consumer Electronic Devices.

FedBoosting: Federated learning with gradient protected boosting for text recognition (2023)
Journal Article
Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569, Article 127126. https://doi.org/10.1016/j.neucom.2023.127126

Conventional machine learning methodologies require the centralization of data for model training, which may be infeasible in situations where data sharing limitations are imposed due to concerns such as privacy and gradient protect... Read More about FedBoosting: Federated learning with gradient protected boosting for text recognition.

Recommender systems for teachers: The relation between social ties and the effectiveness of socially-based features (2023)
Journal Article
Yacobson, E., Toda, A. M., Cristea, A. I., & Alexandron, G. (2024). Recommender systems for teachers: The relation between social ties and the effectiveness of socially-based features. Computers & Education, 210, Article 104960. https://doi.org/10.1016/j.compedu.2023.104960

Open Educational Resources (OER) repositories provide teachers with a wide range of learning resources (LRs), enabling them to design various learning sequences. However, search & select in large OER repositories can be a daunting task for teachers.... Read More about Recommender systems for teachers: The relation between social ties and the effectiveness of socially-based features.

Evaluating ChatGPT text mining of clinical records for companion animal obesity monitoring (2023)
Journal Article
Fins, I. S., Davies, H., Farrell, S., Torres, J. R., Pinchbeck, G., Radford, A. D., & Noble, P. (2023). Evaluating ChatGPT text mining of clinical records for companion animal obesity monitoring. Veterinary Record, Article e3669. https://doi.org/10.1002/vetr.3669

Background: Veterinary clinical narratives remain a largely untapped resource for addressing complex diseases. Here we compare the ability of a large language model (ChatGPT) and a previously developed regular expression (RegexT) to identify overweig... Read More about Evaluating ChatGPT text mining of clinical records for companion animal obesity monitoring.

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, 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.

Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums (2023)
Journal Article
Alrajhi, L., Alamri, A., Pereira, F. D., Cristea, A. I., & Oliveira, E. H. T. (2023). Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums. User Modeling and User-Adapted Interaction, https://doi.org/10.1007/s11257-023-09381-y

In MOOCs, identifying urgent comments on discussion forums is an ongoing challenge. Whilst urgent comments require immediate reactions from instructors, to improve interaction with their learners, and potentially reducing drop-out rates—the task is d... Read More about Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums.

MRL-Seg: Overcoming Imbalance in Medical Image Segmentation With Multi-Step Reinforcement Learning (2023)
Journal Article
Yang, F., Li, X., Duan, H., Xu, F., Huang, Y., Zhang, X., …Zheng, Y. (2024). MRL-Seg: Overcoming Imbalance in Medical Image Segmentation With Multi-Step Reinforcement Learning. IEEE Journal of Biomedical and Health Informatics, 28(2), 858-869. https://doi.org/10.1109/jbhi.2023.3336726

Medical image segmentation is a critical task for clinical diagnosis and research. However, dealing with highly imbalanced data remains a significant challenge in this domain, where the region of interest (ROI) may exhibit substantial variations acro... Read More about MRL-Seg: Overcoming Imbalance in Medical Image Segmentation With Multi-Step Reinforcement Learning.

When in Rome: A Meta-corpus of Functional Harmony (2023)
Journal Article
Gotham, M., Micchi, G., López, N. N., & Sailor, M. (2023). When in Rome: A Meta-corpus of Functional Harmony. Transactions of the International Society for Music Information Retrieval, 6(1), 150-166. https://doi.org/10.5334/tismir.165

‘When in Rome’ brings together all human-made, computer-encoded, functional harmonic analyses of music. This amounts in total to over 2,000 analyses of 1,500 distinct works. The most obvious motivation is scale: gathering these datasets together lead... Read More about When in Rome: A Meta-corpus of Functional Harmony.

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.