-
further insights into their underlying neural mechanisms and computational principles. This Ph.D. research project will focus on two aspects: (i) developing and applying advanced AI and machine learning
-
encryption: A brief survey. IEEE Internet of Things Journal, 11(14), pp.24569-24580. 5. Yang, W., Wang, H., Li, Z., Niu, Z., Wu, L., Wei, X., Su, Y. and Susilo, W., 2024. Privacy-Preserving Machine Learning in
-
research aims to utilize advanced machine learning techniques to understand the intricate behaviours and movements of vultures in the south of Spain, focusing on their feeding, foraging, nesting patterns
-
years, machine learning (ML) methods have been found to be effective in wireless communication, particularly for channel estimation in RIS integrated NOMA communication systems. However, still required
-
equivalent) are NOT eligible to apply for an award. Due consideration should be given to financing your studies . Recommended reading 1. Abbasi, B. and Goldenholz, D.M., 2019. Machine learning applications in
-
Apply and key information This project is funded by: BBSRC/UKRI Doctoral Landscape Award Summary Artificial intelligence (AI) and machine learning (ML) could greatly change how doctors diagnose and
-
, K., Fan, H., Wu, Y., & Xu, D. (2022). "Masked Image Modeling for Self-Supervised Learning of Visual Features." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR
-
. Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study JMIR Med Inform 2020;8(9):e20995 Tobin et al. Co-Clustering Multi-View Data
-
[1] N. Rieke et al., “The Future of Digital Health with Federated Learning,” arXiv Prepr. arXiv2003.08119, 2020. [2] Q. Yang, Y. Liu, T. Chen, and Y. Tong, “Federated machine learning: Concept and
-
to ensure both the privacy of data and the security of the network itself. Federated learning (FL), a decentralised machine learning paradigm, presents a promising solution to these challenges. In contrast