Research Interests:

Artificial intelligence (AI), machine learning (theory and algorithms), deep learning, image processing, computer vision, bioinformatics, human computer interactions (HCI), and information storage and retrieval. My main interest is in investigating better ways of solving real-world problems using computing technologies.

Selected publications:

Blessing Ojeme and Sampson Akwafuo (2023). Time Series Biomedical Imaging and Computational Epidemiology. A workshop paper presentation at the 2023 CMD-IT/ACM Richard Tapia Celebration of Diversity in Computing Conference, Dallas, Texas Sept 13 – 15.

Blessing Ojeme, Frederick Quinn, Russell Karls, and Shannon Quinn (2022). Fully automated methods for the detection and segmentation of Mitochondria in microscopy images. Proceedings of the 16th International Conference on Computer Vision (ICCV 2022). Vancouver, Canada September 22-23, 2022. Pp234-239
https://publications.waset.org/10012940/fully-automated-methods-for-the-detection-and-se gmentation-of-mitochondria-in-microscopy-images

Edvaldo Domingos, Blessing Ojeme, Olawande Daramola (2021). Experimental Analysis of Hyper-parameters for Deep Learning-based Churn Prediction in the Banking Sector. Computation 2021, Vol 9, No 34
https://www.mdpi.com/2079-3197/9/3/34

Agbele Tobechukwu, Blessing Ojeme and Richard Jiang (2019) . Application of local binary patterns and cascade AdaBoost classifier for mice behavioural patterns detection and analysis. Proceedings of the 23rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES-2019). Budapest, Hungary, September 4-6, Vol 159, Page 1375-1386. Available at: https://www.sciencedirect.com/science/article/pii/S187705091931508X?via%3Dihub

Blessing Ojeme, Audrey Mbogho and Thomas Meyer (2016) . Probabilistic Expert Systems for Reasoning in Clinical Depressive Disorders. Proceedings of the The 15th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA'16), Anaheim, California, USA, December 18-20. PP. 599-604. Available at : https://ieeexplore.ieee.org/document/7838209/