240 citations · 274 across the 20 of their papers we have counts for
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A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data
Yusuf Brima, Marcellin Atemkeng, Lakshmana Rao Namamula +1
Dementia is a major and growing global health burden, with Alzheimer's disease (AD) accounting for most cases. Timely and accurate diagnosis is central to managing this burden and…
Unsupervised Detection of Groundwater Storage Anomalies in Ghana Using GRACE Satellite Data
George Yamoah Afrifa, Theophilus Ansah-Narh, Marcellin Atemkeng
Groundwater variability in Ghana remains poorly characterized due to limited long-term in-situ observations. This study investigates groundwater storage anomalies using GRACE-deriv…
Performance Benchmarking and Optimisation of Clustering Algorithms for Local and Non-Local Similarity Measure in Medical Image Analysis
Sisipho Hamlomo, Marcellin Atemkeng
Medical imaging generates high-resolution images posing significant storage, transmission, and computational challenges. While low-rank matrix approximation (LoRMA) techniques offe…
Few-shot Cross-country Generalization of Tabular Machine Learning and Foundation Models for Childhood Anemia Prediction under Distribution Shift
Yusuf Brima, Marcellin Atemkeng, Lansana Hassim Kallon +4
Childhood anemia affects around 40% of children aged 6-59 months globally and arises from heterogeneous factors, limiting model generalizability. We evaluate a transformer-based ta…
Bridging visual saliency and large language models for explainable deep learning in medical imaging
Paul Valery Nguezet, Elie Tagne Fute, Yusuf Brima +2
The opaque nature of deep learning models remains a significant barrier to their clinical adoption in medical imaging. This paper presents a multimodal explainability framework tha…
Unsupervised Electrofacies Classification and Porosity Characterization in the Offshore Keta Basin Using Wireline Logs
Hamdiya Adams, Theophilus Ansah-Narh, Daniel Kwadwo Asiedu +6
This study presents an unsupervised machine learning workflow for electrofacies analysis in the offshore Keta Basin, Ghana, where core data are scarce. Six standard wireline logs f…
Anomaly Detection in Soil Heavy Metal Contamination Using Unsupervised Learning for Environmental Risk Assessment
Isaac Tettey Adjokatse, Samuel Senyo Koranteng, George Yamoah Afrifa +6
Soil contamination by heavy metals poses a persistent environmental and public health concern in rapidly urbanising regions of Ghana, particularly at unregulated waste disposal sit…
Hierarchical Spatio-Channel Clustering for Efficient Model Compression in Medical Image Analysis
Sisipho Hamlomo, Marcellin Atemkeng, Habte Tadesse Likassa +5
Convolutional neural networks (CNNs) have become increasingly difficult to deploy in resource-constrained environments due to their large memory and computational requirements. Alt…
Balancing Performance and Fairness in Explainable AI for Anomaly Detection in Distributed Power Plants Monitoring
Corneille Niyonkuru, Marcellin Atemkeng, Gabin Maxime Nguegnang +1
Reliable anomaly detection in distributed power plant monitoring systems is essential for ensuring operational continuity and reducing maintenance costs, particularly in regions wh…
An Optimised Greedy-Weighted Ensemble Framework for Financial Loan Default Prediction
Ezekiel Nii Noye Nortey, Jones Asante-Koranteng, Marcellin Atemkeng +4
Accurate prediction of loan defaults is a central challenge in credit risk management, particularly in modern financial datasets characterised by nonlinear relationships, class imb…