AI Research Group

Dr Juan Ye

Dr Juan Ye

Dr Juan Ye

Senior Lecturer - School of Computer Science

Full research profile

Email: jy31@st-andrews.ac.uk

Office: JC1.12

Phone: +44 (0)1334 463258

Web: https://ye.host.cs.st-andrews.ac.uk

Recent Publications

Fang, L, Liu, X, Su, X, Ye, J , Dobson, S, Hui, P & Tarkoma, S 2021, Bayesian inference federated learning for heart rate prediction. in J Ye, MJ O'Grady, G Civitarese & K Yordanova (eds), Wireless Mobile Communication and Healthcare: 9th EAI International Conference, MobiHealth 2020, Virtual Event, November 19, 2020, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 362 LNICST, Springer, Cham, pp. 116-130. https://doi.org/10.1007/978-3-030-70569-5_8
Ye, J, Nakwijit, P, Schiemer, M, Jha, S & Zambonelli, F 2021, 'Continual activity recognition with generative adversarial networks', ACM Transactions on Internet of Things, vol. 2, no. 2, 9, pp. 1-25. https://doi.org/10.1145/3440036
Jha, S, Schiemer, M, Zambonelli, F & Ye, J 2021, 'Continual learning in sensor-based human activity recognition: an empirical benchmark analysis', Information Sciences, vol. In Press, pp. 1-35. https://doi.org/10.1016/j.ins.2021.04.062
Mansouri Benssassi, E & Ye, J 2021, 'Generalisation and robustness investigation for facial and speech emotion recognition using bio-inspired spiking neural networks', Soft Computing, vol. First Online. https://doi.org/10.1007/s00500-020-05501-7
Ye, J 2021, 'Shared learning activity labels across heterogeneous datasets', Journal of Ambient Intelligence and Smart Environments, vol. Pre-press, pp. 1-18. https://doi.org/10.3233/AIS-210590
Rosales Sanabria, A, Zambonelli, F & Ye, J 2021, 'Unsupervised domain adaptation in activity recognition: a GAN-based approach', IEEE Access, vol. 9, pp. 19421-19438. https://doi.org/10.1109/ACCESS.2021.3053704
Jha, S, Schiemer, M & Ye, J 2020, Continual learning in human activity recognition: an empirical analysis of regularization. in Proceedings of Machine Learning Research. pp. 1-4, Thirty-seventh International Conference on Machine Learning, ICML 2020; ICML Workshop on Continual Learning, 13/07/20.
Fang, L , Ye, J & Dobson, SA 2020, 'Discovery and recognition of emerging human activities using a hierarchical mixture of directional statistical models', IEEE Transactions on Knowledge and Data Engineering, vol. 32, no. 7, pp. 1304 - 1316. https://doi.org/10.1109/TKDE.2019.2905207
Ye, J & Callus, E 2020, 'Evolving models for incrementally learning emerging activities', Journal of Ambient Intelligence and Smart Environments, vol. 12, no. 4, pp. 313-325. https://doi.org/10.3233/AIS-200566
Ye, J, O’Grady, M & Banos, O 2020, 'Sensor technology for smart homes', Sensors, vol. 20, no. 24, 7046. https://doi.org/10.3390/s20247046