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Selected Peer-reviewed Publications in top conferences:

Z. Jiang, H. Rahmani, P. Angelov, S. Black, B. Williams, Graph-context Attention Networks for Size-varied Deep Graph Matching, CVPR 2022, 19-24 June 2022, New Orleans, USA, pp. 2343-2352

​A. Lopez Pellicer, Y. Li, P. Angelov, PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection, CVPR-W, 2024, pp. 3809-3817, DOI: 10.1109/CVPRW63382.2024.00385

Y. Li, P. Angelov, N. Suri, Robust Self-Supervised Learning for Adversarial Attack Detection, NeurIPS – 2024, 5th Workshop on Self-supervised Learning: Theory and Practice.

D. Kangin, P. Angelov, Unsupervised Domain Adaptation within Deep Foundation Latent Spaces, ICLR-W, Vienna, Austria, 11 May 2024.

D. Kangin, A. Aghasanli, P. Angelov, Interpretable-through-prototypes deepfake detection for diffusion models, ICCV-W 2023, 2 Oct. 2023, pp.467-474.

J. P. Klock, J. P. Pinto, J. Moura, Y. Li, C. Castro, P. Angelov, Vision-based Landing Guidance through Tracking and Orientation Estimation, WACV-2025, Tucson, AZ, USA, March 2025.

Y. Li, Y. Sun, P. Angelov, Complex-Cycle-Consistent Diffusion Model for Monaural Speech Enhancement, The 39th AAAI Conference on AI, Philadelphia, PA, USA, 27 Feb – 2 March 2025.

Y. Li, P. Angelov, S. Neeraj, Rethinking Self-supervised Learning for Cross-domain Adversarial Sample Recovery, IJCNN 2024, Yokohama, Japan, 1-5 July 2024, DOI: 10.1109/IJCNN60899.2024.10650687

R. D. Baruah, P. Angelov, Evolving Local Means Method for Clustering of Streaming Data, In Proc. WCCI-2012, 10-15 June 2012, Brisbane, Australia, pp.2161-2168 (IEEE Press ISBN 978-1-4673-1489-3).

Y. Li, P. Angelov, N. Suri, Self-supervised representation learning for adversarial attack detection, 18th ECCV, Milano, Italy, Sept 29 – Oct 4, 2024, Proceedings, Part LX , DOI: 10.1007/978-3-031-73027-6_14, 236-252

N. L. Baisa, B. Williams, H. Rahmani, P. Angelov, S. Black, Multi-branch with attention network for hand-based person recognition, ICPR 2022, pp.727-732, IEEE Press, Aug. 2022.

N. L. Baisa, B. Williams, H. Rahmani, P. Angelov, S. Black, Hand-based person identification using global and part-aware deep feature representation learning, 2022 Eleventh IPTA, 19-22 April 2022, DOI 10.1109/IPTA54936.2022.9784133.

P. Angelov, E. Soares, Towards Deep Machine Reasoning: a Prototype-based Deep Neural Network with Decision Tree Inference, IEEE SMC2020, 11-14 Oct 2020, Toronto, Canada, pp. 2092-2099, DOI: 10.1109/SMC42975.2020. 9282812.

E. Soares, P. Angelov, N. Suri, Similarity-based Deep Neural Network to Detect Imperceptible Adversarial Attacks, SCCI2022, 4-7 Dec. 2022, Singapore, DOI: 10.1109/SSCI51031.2022.10022016.

M. C. Alves, E. S. Yourdshahi, A. Varma, L. S. Marcolino, J. Ueyama, P. Angelov, On-line estimators for ad-hoc task execution: learning types and parameters of teammates for effective teamwork, Proc. 2023 AAMAS, pp.140-142, May 2023.

Z. Yu, Y. Lu, P. Angelov, N. Suri, PPFM: An Adaptive and Hierarchical Peer-to-Peer Federated Meta-Learning Framework, 18th MSN, Guangzhou, China, 14-16 Dec. 2022, best paper award​

R. Vyas, H. Rahmani, R Boswell-Challand, P. Angelov, S Black, B. M. Williams, Robust End-to-End Hand Identification via Holistic Multi-Unit Knuckle Recognition, 2021 IJCB, Aug. 2021, pp. 1-8.

E. Soares, P. Angelov, D. Filev, B. Costa, M. Castro, S. Nageshrao, Explainable Density-based Approach for Self-driving actions classification, 2019 ICMLA, 16 Dec 2019, pp. 469-474.  

E. S. Yourdshahi, T. Pinder, G. Dhawan, L. S. Marcolino, P. Angelov, Towards Large Scale Ad-hoc Teamwork, 2018 ICA, Singapore, pp.44-49.​

Y. Li, P. Angelov, Z. Yu, A. Lopez Pellicer, N. Suri, Federated adversarial learning for robust autonomous landing runway detection, In: Proc. 33rd ICANN Lugano, Switzerland, 17-20 Sept. 2024, Part VI, 159-173, DOI: 10.1007/978-3-031-72347-6_11

B. Tomczyk, P. Angelov, D. Kangin, Machine Learning within Latent spaces formed by Foundation Models, 12th IEEE-IS’24, Varna, Bulgaria, 29-31 Aug. 2024, DOI: 10.1109/IS61756.2024.10705264

Lancaster University

© 2015 by Plamen Angelov

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