| Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward. E Elyan, P Vuttipittayamongkol, P Johnston, K Martin, K McPherson, ... Artificial Intelligence Surgery 2, 2022 | 67 | 2022 |
| A review of digital video tampering: From simple editing to full synthesis P Johnston, E Elyan Digital Investigation 29, 67-81, 2019 | 49 | 2019 |
| A review of state-of-the-art in Face Presentation Attack Detection: From early development to advanced deep learning and multi-modal fusion methods F Abdullakutty, E Elyan, P Johnston Information fusion 75, 55-69, 2021 | 44 | 2021 |
| Video tampering localisation using features learned from authentic content P Johnston, E Elyan, C Jayne Neural computing and applications 32 (16), 12243-12257, 2020 | 26 | 2020 |
| Fusion methods for face presentation attack detection F Abdullakutty, P Johnston, E Elyan Sensors 22 (14), 5196, 2022 | 11 | 2022 |
| Deep transfer learning on the aggregated dataset for face presentation attack detection F Abdullakutty, E Elyan, P Johnston, A Ali-Gombe Cognitive computation 14 (6), 2223-2233, 2022 | 9 | 2022 |
| Symbols in engineering drawings (SIED): an imbalanced dataset benchmarked by convolutional neural networks E Elyan, CF Moreno-García, P Johnston Proceedings of the 21st EANN (Engineering Applications of Neural Networks …, 2020 | 7 | 2020 |
| Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks I Carloto, P Johnston, CJ Pestana, LA Lawton Science of The Total Environment 784, 146956, 2021 | 6 | 2021 |
| Spatial effects of video compression on classification in convolutional neural networks P Johnston, E Elyan, C Jayne 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 5 | 2018 |
| Face spoof detection: an experimental framework F Abdullakutty, E Elyan, P Johnston International Conference on Engineering Applications of Neural Networks, 293-304, 2021 | 3 | 2021 |
| Pixel-based layer segmentation of complex engineering drawings using convolutional neural networks CF Moreno-García, P Johnston, B Garkuwa 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 3 | 2020 |
| Toward video tampering exposure: inferring compression parameters from pixels P Johnston, E Elyan, C Jayne Engineering Applications of Neural Networks: 19th International Conference …, 2018 | 2 | 2018 |
| Unmasking the Imposters: Task-specific feature learning for face presentation attack detection F Abdullakutty, E Elyan, P Johnston 2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023 | 1 | 2023 |
| Generalisation challenges in deep learning models for medical imagery: insights from external validation of COVID-19 classifiers SC Haynes, P Johnston, E Elyan Multimedia Tools and Applications, 1-20, 2024 | | 2024 |
| Exploring independent learning (IL) and its relationship to mindset, motivated strategies for learning and academic performance KE Forbes-McKay, PAM Bremner, P Johnston, C Air Journal of Applied Research in Higher Education, 2023 | | 2023 |
| Student interaction with a virtual learning environment: An empirical study of online engagement behaviours during and since the time of COVID-19 P Johnston, M Zarb, CF Moreno-Garcia 2023 IEEE Frontiers in Education Conference (FIE), 1-8, 2023 | | 2023 |
| Exploring students' independent learning and its relationship to mindset and academic performance. KE Forbes-McKay, P Bremner, P Johnston | | 2023 |
| Enhancing our understanding of independent learning amongst RGU students. K Forbes-McKay, P Bremner, P Johnston | | 2022 |
| Beyond the pixels: learning and utilising video compression features for localisation of digital tampering. P Johnston | | 2019 |
Eyad ElyanEyad Elyan, Professor, School of Computing, Robert Gordon UniversityVerified email at rgu.ac.uk
