@article{CRSIJ26000204,
                  author = {Adeyemi, Biliqees Temitope, Ipeayeda Funmilola W., Oyediran Mayowa O.},
                  title = {Robust Multimodal Authentication Under Adverse Conditions: An Optimised Neural Fusion Model Integrating Fingerprint, Facial and OCR Verification},
                  journal = {Cosmo Research and Science International Journal},
                  year = {2025},
                  volume = {1},
                  number = {6},
                  pages = {503-518},
                  issn = {3108-1584},
                  url = {https://cosmorsij.com/published/CRSIJ26000204.pdf},
                  abstract = {With the advent of learning moving to the digital realm, there is an increased threat of security at educational institutions, necessitating a more efficient method beyond just passwords. Unimodal biometric systems offer an alternative but inherit a single point of failure that degrades under adverse conditions, a limitation of particular consequence for educational institutions in developing economies. This study developed and empirically evaluated an optimized Artificial Neural Network for a three-level authentication scheme integrating fingerprint, facial, and Optical Character Recognition modalities through early feature-level fusion. A multilayer perceptron was trained using the Adam optimizer, L2 regularization, dropout, and early stopping, with fusion weights set by deterministic grid search on a held-out validation set. The model was evaluated on the NIST SD4, Labelled Faces in the Wild, and IAM benchmarks under optimal, low-light, and high-noise conditions. The fused system achieved 98.2 per cent accuracy at a 0.7 per cent false acceptance rate, sustaining 97.8 and 96.5 per cent under low-light and high-noise conditions respectively. It significantly reduced the false acceptance rate relative to every individual modality, a result confirmed by Welch's F-test under unequal variances, while exhibiting substantially narrower error variance, indicating that fusion both improves and stabilizes security.},
                  keywords = {Authentication, multimodal, multilayer, biometric, security, fusion, unimodal},
                  month = {May}
        }