| 2025 | CVPR | Prototype-Based Continual Learning with Label-free Replay Buffer and Cluster Preservation Loss. | Agil Aghasanli, Yi Li, Plamen Angelov |
| 2025 | ICCV | ProtoMedX: Towards Explainable Multi-Modal Prototype Learning for Bone Health Classification. | Alvaro Lopez Pellicer, Andre Mariucci, Plamen Angelov, Marwan Bukhari, Jemma G. Kerns |
| 2025 | IJCNN | Detecting Cross-domain Deepfake Videos with Contrastive Prototype Learning. | Yi Li, Plamen Angelov |
| 2025 | WACV | Vision-Based Landing Guidance Through Tracking and Orientation Estimation. | Joo P. K. Ferreira, Joo P. L. Pinto, Jlia S. Moura, Yi Li, Cristiano Leite Castro, Plamen Angelov |
| 2024 | CVPR | PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection. | Alvaro Lopez Pellcier, Yi Li, Plamen Angelov |
| 2024 | ECCV | Self-supervised Representation Learning for Adversarial Attack Detection. | Yi Li, Plamen Angelov, Neeraj Suri |
| 2024 | ESANN | Unsupervised Drift Detection Using Quadtree Spatial Mapping. | Bernardo A. Ramos, Cristiano Leite de Castro, Tiago A. Coelho, Plamen Angelov |
| 2024 | ICANN | Federated Adversarial Learning for Robust Autonomous Landing Runway Detection. | Yi Li, Plamen Angelov, Zhengxin Yu, Alvaro Lopez Pellicer, Neeraj Suri |
| 2024 | IJCNN | Rethinking Self-supervised Learning for Cross-domain Adversarial Sample Recovery. | Yi Li, Plamen Angelov, Neeraj Suri |
| 2024 | IJCNN | UNICAD: A Unified Approach for Attack Detection, Noise Reduction and Novel Class Identification. | Alvaro Lopez Pellicer, Kittipos Giatgong, Yi Li, Neeraj Suri, Plamen Angelov |
| 2023 | IJCNN | Domain Generalization and Feature Fusion for Cross-domain Imperceptible Adversarial Attack Detection. | Yi Li, Plamen Angelov, Neeraj Suri |
| 2022 | CVPR | Graph-context Attention Networks for Size-varied Deep Graph Matching. | Zheheng Jiang, Hossein Rahmani, Plamen Angelov, Sue Black, Bryan M. Williams |
| 2022 | ICPR | Multi-Branch with Attention Network for Hand-Based Person Recognition. | Nathanael L. Baisa, Bryan M. Williams, Hossein Rahmani, Plamen Angelov, Sue Black |
| 2021 | PERCOM | Keynote: Explainable-by-design Deep Learning. | Plamen Angelov |
| 2020 | ICAISC | Concept Drift Detection Using Autoencoders in Data Streams Processing. | Maciej Jaworski, Leszek Rutkowski, Plamen Angelov |
| 2020 | SMC | Towards Deep Machine Reasoning: a Prototype-based Deep Neural Network with Decision Tree Inference. | Plamen Angelov, Eduardo A. Soares |
| 2019 | ICMLA | Explainable Density-Based Approach for Self-Driving Actions Classification. | Eduardo A. Soares, Plamen Angelov, Dimitar P. Filev, Bruno Costa, Marcos Castro, Subramanya Nageshrao |
| 2019 | IJCNN | Actively Semi-Supervised Deep Rule-based Classifier Applied to Adverse Driving Scenarios. | Eduardo A. Soares, Plamen Angelov, Bruno Costa, Marcos Castro |
| 2018 | ENASE | Empirical Approach to Learning from Data (Streams). | Plamen Angelov |
| 2018 | SMC | A Deep Rule-Based Approach for Satellite Scene Image Analysis. | Xiaowei Gu, Plamen Angelov |
| 2017 | IJCNN | Fast feedforward non-parametric deep learning network with automatic feature extraction. | Plamen Angelov, Xiaowei Gu, Jos C. Prncipe |
| 2017 | IJCNN | Human action recognition using transfer learning with deep representations. | Allah Bux Sargano, Xiaofeng Wang, Plamen Angelov, Zulfiqar Habib |
| 2017 | SMC | A cascade of deep learning fuzzy rule-based image classifier and SVM. | Plamen Angelov, Xiaowei Gu |
| 2016 | ESANN | Challenges in Deep Learning. | Plamen Angelov, Alessandro Sperduti |
| 2016 | IJCNN | A general purpose intelligent surveillance system for mobile devices using Deep Learning. | Antreas Antoniou, Plamen Angelov |
| 2016 | SMC | Empirical data analysis: A new tool for data analytics. | Plamen Angelov, Xiaowei Gu, Dmitry Kangin, Jos C. Prncipe |
| 2015 | IJCNN | Typicality distribution function - A new density-based data analytics tool. | Plamen Angelov |
| 2015 | IJCNN | Evolving clustering, classification and regression with TEDA. | Dmitry Kangin, Plamen Angelov |
| 2015 | SMC | Edge Flow. | Gruffydd Morris, Plamen Angelov |
| 2014 | SMC | Real-time novelty detection in video using background subtraction techniques: State of the art a practical review. | Gruffydd Morris, Plamen Angelov |
| 2013 | ICANN | Vehicle Plate Recognition Using Improved Neocognitron Neural Network. | Dmitry Kangin, George Kolev, Plamen Angelov |
| 2013 | ICANN | OSA: One-Class Recursive SVM Algorithm with Negative Samples for Fault Detection. | Mikhail Suvorov, Sergey Ivliev, Garegin Markarian, Denis Kolev, Dmitry Zvikhachevskiy, Plamen Angelov |
| 2013 | IJCNN | Incremental anomaly identification by adapted SVM method. | Mikhail Suvorov, Sergey Ivliev, Garegin Markarian, Denis Kolev, Dmitry Zvikhachevskiy, Plamen Angelov |
| 2011 | IJCCI | Autonomous Learning Machines - Generating Rules from Data Streams. | Plamen Angelov |
| 2011 | SMC | Simpl_eClass: Simplified potential-free evolving fuzzy rule-based classifiers. | Rashmi Dutta Baruah, Plamen Angelov, Javier Andreu |
| 2010 | ECAI | Human Activity Recognition in Intelligent Home Environments: An Evolving Approach. | Jos Antonio Iglesias, Plamen Angelov, Agapito Ledezma, Araceli Sanchis |
| 2010 | IPMU | A Fast Recursive Approach to Autonomous Detection, Identification and Tracking of Multiple Objects in Video Streams under Uncertainties. | Pouria Sadeghi-Tehran, Plamen Angelov, Ramin Ramezani |
| 2009 | EUSFLAT | Detecting and Reacting on Drifts and Shifts in On-Line Data Streams with Evolving Fuzzy Systems. | Edwin Lughofer, Plamen Angelov |
| 2008 | IJCNN | Autonomous novelty detection and object tracking in video streams using evolving clustering and Takagi-Sugeno type neuro-fuzzy system. | Plamen Angelov, Ramin Ramezani, Xiaowei Zhou |
| 2007 | SMC | Architectures for evolving fuzzy rule-based classifiers. | Plamen Angelov, Xiaowei Zhou, Dimitar P. Filev, Edwin Lughofer |
| 2007 | SMC | Soft sensor for predicting crude oil distillation side streams using evolving takagi-sugeno fuzzy models. | Jos J. Macias-Hernandez, Plamen Angelov, Xiaowei Zhou |
| 2006 | ICDM | Evolving Extended Naive Bayes Classifiers. | Frank Klawonn, Plamen Angelov |
| 2003 | IFSA | On-line Design of Takagi-Sugeno Models. | Plamen Angelov, Dimitar P. Filev |