Selected Publications
Selected Publications
Below is a selection of my peer-reviewed research publications in the fields of machine learning, computer vision, deep learning, and applied AI. For a comprehensive list, please visit my Google Scholar profile.
2025
M.R. Shuvo, M.S. Mekala & E. Elyan. Deep Learning and Attention-Based Methods for Human Activity Recognition and Anticipation: A Comprehensive Review. Cogn Comput 17, 158 (2025).
DOI Link | PDFM.R. Shuvo, M.S. Mekala & E. Elyan, MSBATN: Multi-Stage Boundary-Aware Transformer Network for action segmentation in untrimmed surgical videos. Computer Vision and Image Understanding,
Volume 261, DOI Link | PDFI. Ekeke, C.F. Moreno-García, E. Elyan (2026). KD-LSRED : Knowledge Distillation for Lightweight Symbol Recognition in Engineering Diagrams. In: X.C. Yin, D. Karatzas, D. Lopresti (eds) Document Analysis and Recognition – ICDAR 2025. ICDAR 2025. Lecture Notes in Computer Science, vol 16027. Springer, Cham. DOI Link | PDF
2024
H. Farhadi Tolie, J. Ren, E. Elyan, DICAM: Deep Inception and Channel-wise Attention Modules for underwater image enhancement, Neurocomputing, Volume 584, 2024, 127585, ISSN 0925-2312, DOI Link | PDF
L. Jamieson, C.F. Moreno-García & E. Elyan. A review of deep learning methods for digitisation of complex documents and engineering diagrams. Artificial Intelligence Review 57, 136 (2024). DOI Link | PDF
2023
- F. Abdullakutty, E. Elyan and P. Johnston, “Unmasking the Imposters: Task-specific feature learning for face presentation attack detection,” 2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia, 2023, pp. 1-8, DOI Link | PDF
2022
- E. Elyan, P. Vuttipittayamongkol, P. Johnston, K. Martin, K. McPherson, C.F. Moreno-García, C. Jayne, M.K. Sarker. Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward. Art Int Surg. 2022;2:24-45. DOI Link | PDF
2021
- F. Abdullakutty, E. Elyan, P. Johnston, A review of state-of-the-art in Face Presentation Attack Detection: From early development to advanced deep learning and multi-modal fusion methods, Information Fusion, Volume 75, 2021, Pages 55-69, DOI Link | PDF
2020
- E. Elyan, L. Jamieson, A. Ali-Gombe, Deep learning for symbols detection and classification in engineering drawings, Neural Networks, Volume 129, 2020, Pages 91-102, DOI Link | PDF
2019
- A. Ali-Gombe, E. Elyan, MFC-GAN: Class-imbalanced dataset classification using Multiple Fake Class Generative Adversarial Network, Neurocomputing, Volume 361, 2019, Pages 212-221, DOI Link | PDF
2018
- E. Elyan, C.M. Garcia and C. Jayne, “Symbols Classification in Engineering Drawings,” 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, 2018, pp. 1-8, DOI Link | PDF
2017
- E. Elyan, M.M. Gaber, A genetic algorithm approach to optimising random forests applied to class engineered data,
Information Sciences, Volume 384, 2017, ages 220-234, DOI Link | PDF
2016