| Empirical approach to machine learning PP Angelov, X Gu Springer, 2019 | 104 | 2019 |
| Empirical data analytics P Angelov, X Gu, D Kangin International Journal of Intelligent Systems 32 (12), 1261-1284, 2017 | 102 | 2017 |
| Autonomous learning multimodel systems from data streams PP Angelov, X Gu, JC Principe IEEE Transactions on Fuzzy Systems 26 (4), 2213-2224, 2017 | 93 | 2017 |
| Deep rule-based classifier with human-level performance and characteristics PP Angelov, X Gu Information Sciences 463, 196-213, 2018 | 84 | 2018 |
| Self-organising fuzzy logic classifier X Gu, PP Angelov Information Sciences 447, 36-51, 2018 | 80 | 2018 |
| A generalized methodology for data analysis PP Angelov, X Gu, JC Príncipe IEEE transactions on cybernetics 48 (10), 2981-2993, 2017 | 77 | 2017 |
| Robust unsupervised small area change detection from SAR imagery using deep learning X Zhang, H Su, C Zhang, X Gu, X Tan, PM Atkinson ISPRS Journal of Photogrammetry and Remote Sensing 173, 79-94, 2021 | 64 | 2021 |
| A method for autonomous data partitioning X Gu, PP Angelov, JC Príncipe Information sciences 460, 65-82, 2018 | 64 | 2018 |
| Blind Estimation of Pseudo-random Code in Periodic Long Code Direct Sequence Spread Spectrum Signals X Gu, Z Zhao, L Shen IET Communications, 2016 | 61 | 2016 |
| A massively parallel deep rule-based ensemble classifier for remote sensing scenes X Gu, PP Angelov, C Zhang, PM Atkinson IEEE Geoscience and Remote Sensing Letters 15 (3), 345-349, 2018 | 57 | 2018 |
| Empirical data analysis: A new tool for data analytics P Angelov, X Gu, D Kangin, J Principe 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016 | 57 | 2016 |
| A self‐adaptive synthetic over‐sampling technique for imbalanced classification X Gu, PP Angelov, EA Soares International Journal of Intelligent Systems 35 (6), 923-943, 2020 | 55 | 2020 |
| Semi-supervised deep rule-based approach for image classification X Gu, PP Angelov Applied Soft Computing 68, 53-68, 2018 | 53 | 2018 |
| Autonomous learning multiple-model zero-order classifier for heart sound classification E Soares, P Angelov, X Gu Applied Soft Computing 94, 106449, 2020 | 46 | 2020 |
| A new integrated multi-attribute decision-making approach for mobile medical app evaluation under q-rung orthopair fuzzy environment G Tang, Y Yang, X Gu, F Chiclana, P Liu, F Wang Expert Systems with Applications 200, 117034, 2022 | 42 | 2022 |
| Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape Z Wu, C Zhang, X Gu, I Duporge, LF Hughey, JA Stabach, AK Skidmore, ... Nature communications 14 (1), 3072, 2023 | 39 | 2023 |
| A self-training hierarchical prototype-based approach for semi-supervised classification X Gu Information Sciences 535, 204-224, 2020 | 38 | 2020 |
| Interval type-2 fuzzy programming method for risky multicriteria decision-making with heterogeneous relationship G Tang, J Long, X Gu, F Chiclana, P Liu, F Wang Information Sciences 584, 184-211, 2022 | 37 | 2022 |
| Self-organizing fuzzy inference ensemble system for big streaming data classification X Gu, P Angelov, Z Zhao Knowledge-Based Systems 218, 106870, 2021 | 36 | 2021 |
| Toward anthropomorphic machine learning PP Angelov, X Gu Computer 51 (9), 18-27, 2018 | 36 | 2018 |
Plamen P AngelovChair Professor in Intelligent Systems, School of Computing and Communications, Lancaster UniversityVerified email at lancaster.ac.uk
