Outputs (833)

A comprehensive survey for Hyperspectral Image Classification: The evolution from conventional to transformers and Mamba models (2025)
Journal Article
Ahmad, M., Distefano, S., Khan, A. M., Mazzara, M., Li, C., Li, H., Aryal, J., Ding, Y., Vivone, G., & Hong, D. (2025). A comprehensive survey for Hyperspectral Image Classification: The evolution from conventional to transformers and Mamba models. Neurocomputing, 644, Article 130428. https://doi.org/10.1016/j.neucom.2025.130428

Hyperspectral Image Classification (HSIC) presents significant challenges owing to the high dimensionality and intricate nature of Hyperspectral data. While traditional Machine Learning (TML) approaches have demonstrated effectiveness, they often enc... Read More about A comprehensive survey for Hyperspectral Image Classification: The evolution from conventional to transformers and Mamba models.

PD-type iterative learning consensus control approach for an electromechanical actuator-based multiagent system (2025)
Journal Article
Li, B., Riaz, S., Saleem, O., Zhao, Y., & Iqbal, J. (2025). PD-type iterative learning consensus control approach for an electromechanical actuator-based multiagent system. Applied Intelligence, 55(7), Article 684. https://doi.org/10.1007/s10489-025-06559-2

Achieving consensus tracking control of a multiagent system (MAS) is challenging. This article proposes an innovative consensus control scheme of a MAS that is composed of electromechanical actuators. The open-loop derivative-type iterative learning... Read More about PD-type iterative learning consensus control approach for an electromechanical actuator-based multiagent system.

DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification (2025)
Journal Article
Ahmad, M., Mazzara, M., Distefano, S., Khan, A. M., & Ullo, S. L. (in press). DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 10419-10428. https://doi.org/10.1109/JSTARS.2025.3558889

Hyperspectral image classification (HSIC) presents significant challenges due to spectral redundancy and spatial discontinuity, both of which can negatively impact classification performance. To mitigate these issues, this work proposes the Different... Read More about DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image Classification.

LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing (2025)
Journal Article
Niaz, F., Zhang, J., Khalid, M., Younas, M., & Majid, A. (online). LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing. IEEE internet of things journal, https://doi.org/10.1109/JIOT.2025.3549374

Traditional RF-based liquid identification methods generally rely on a single characteristic such as refractive index or permittivity and often assume prior container knowledge, limiting their versatility. These approaches also face challenges in sce... Read More about LiqState: Liquid Identification and State Monitoring Using mmWave IoT Sensing.

Scaling up and automating formative assessment in computer science (2025)
Book Chapter
Gordon, N. (2025). Scaling up and automating formative assessment in computer science. In S. Elkington, & A. Irons (Eds.), Formative Assessment and Feedback in Post-Digital Learning Environments: Disciplinary Case Studies in Higher Education (172-178). Routledge. https://doi.org/10.4324/9781003360254-22

The rise in student numbers in computer science creates a challenge for delivery. Computer science has some of the worst attainment and retention profiles across subjects. Given its technology focus, it is a subject where digital technologies have lo... Read More about Scaling up and automating formative assessment in computer science.

Adaptive reconfigurable learning algorithm for robust optimal longitudinal motion control of UAVs (2025)
Journal Article
Saleem, O., Tanveer, A., & Iqbal, J. (2025). Adaptive reconfigurable learning algorithm for robust optimal longitudinal motion control of UAVs. Algorithms, 18(4), Article 180. https://doi.org/10.3390/a18040180

This study presents the formulation and verification of a novel online adaptive reconfigu-rable learning control algorithm (RLCA) for improved longitudinal motion control and disturbance compensation in unmanned aerial vehicles (UAVs). The proposed a... Read More about Adaptive reconfigurable learning algorithm for robust optimal longitudinal motion control of UAVs.

Spatial-spectral morphological mamba for hyperspectral image classification (2025)
Journal Article
Ahmad, M., Butt, M. H. F., Khan, A. M., Mazzara, M., Distefano, S., Usama, M., Roy, S. K., Chanussot, J., & Hong, D. (online). Spatial-spectral morphological mamba for hyperspectral image classification. Neurocomputing, Article 129995. https://doi.org/10.1016/j.neucom.2025.129995

Recent advancements in transformers, specifically self-attention mechanisms, have significantly improved hyperspectral image (HSI) classification. However, these models often have inefficiencies, as their computational complexity scales quadratically... Read More about Spatial-spectral morphological mamba for hyperspectral image classification.

Comprehensive Health Tracking Through Machine Learning and Wearable Technology (2025)
Journal Article
Yusuf, A., Jaber, T. A., & Gordon, N. (online). Comprehensive Health Tracking Through Machine Learning and Wearable Technology. Journal of Data Science and Intelligent Systems, https://doi.org/10.47852/bonviewjdsis52023588

The accurate interpretation of data from wearable devices is paramount in advancing personalized healthcare and disease prevention. This study explores the application of machine learning techniques to improve the interpretation of health metrics fro... Read More about Comprehensive Health Tracking Through Machine Learning and Wearable Technology.

An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications † (2025)
Journal Article
Arshad, M., Liu, |., Khalid, |. M., Liu, Y., Wang, P., & Arshad, M. (online). An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications †. International Journal of Satellite Communications and Networking, https://doi.org/10.1002/sat.1560

Satellite communication has gained significant attention in the context of sixth-generation (6G) internet technology. Due to their high altitudes, dynamic link switching, and limited resources, satellite nodes are prone to higher bit error rates and... Read More about An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications †.

Evaluating and implementing machine learning models for personalised mobile health app recommendations (2025)
Journal Article
Morenigbade, H., Al Jaber, T., Gordon, N., & Eke, G. (2025). Evaluating and implementing machine learning models for personalised mobile health app recommendations. PLoS ONE, 20(3 March), Article e0319828. https://doi.org/10.1371/journal.pone.0319828

This paper focuses on the evaluation and recommendation of healthcare applications in the mHealth field. The increase in the use of health applications, supported by an expanding mHealth market, highlights the importance of this research. In this stu... Read More about Evaluating and implementing machine learning models for personalised mobile health app recommendations.