Ogban-Asuquo Ugot
Member
Ogban is a deep learning researcher with a B.Tech in Mechatronics engineering (Bells University Ota), PGD Computer Science (UNILAG) and MSC Computer science (UNILAG). He has coauthored peer reviewed papers in the areas of computer vision, adversarial neural networks and recurrent neural networks and has attended academic conferences where he presented his work. Ogban is also a passionate software engineer with over 6 years experience applying deep learning algorithms to real world problems.
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Publications
1. Ugot OA., and Yinka-Banjo, C., “Biometric Fingerprint Generation using Generative Adversarial Networks. Springer; Artificial Intelligence for Cyber Security: Methods, Issues and Possible Horizons or Opportunities (AIC), to be published May 2021.
2. Akinyemi, M., Yinka-Banjo, C., Ugot, O.A. and Nwachuku, A., 2020, March. Estimating the Time Lapse Between Medical Insurance Reimbursement with Non-parametric Regression Models. In Future of Information and Communication Conference (pp. 692-704). Springer, Cham.
3. Yinka-Banjo, C., Ugot, O.A., Misra, S., Adewumi, A., Damasevicius, R. and Maskeliunas, R., 2019, June. Conflict resolution via emerging technologies?. In Journal of Physics: Conference Series (Vol.1235, No. 1, p. 012022). IOP Publishing.
4. Yinka-Banjo, C. and Ugot, O.A., 2019. A review of generative adversarial networks and its application in cybersecurity. Artificial Intelligence Review, pp.1-16.
5. Yinka-Banjo, C., and Ugot, O., 2018, ‘ A Predictive Model for Automatic Generation Control in Smart Grids using Artificial Neural Networks’, AFRICATEK 2018: 2nd EAI International Conference on Emerging Technologies for Developing Countries, Cotonou, Benin.