240 citations · 274 across the 20 of their papers we have counts for
11 papers · 1 filter
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…
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…
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…
An Empirical Study of Machine Learning Robustness and Scalability for Imbalanced Tabular Clinical Data in Emergency and Critical Care
Yusuf Brima, Marcellin Atemkeng
Every year, millions of patients pass through emergency departments and intensive care units, where clinicians must make high-stakes decisions under time pressure and uncertainty.…
Clustering-Based Low-Rank Matrix Approximation for Medical Image Compression
Sisipho Hamlomo, Marcellin Atemkeng
Medical images are inherently high-resolution and contain locally varying structures crucial for diagnosis. Efficient compression must preserve diagnostic fidelity while minimizing…
Unsupervised anomaly detection in large-scale estuarine acoustic telemetry data
Siphendulwe Zaza, Marcellin Atemkeng, Taryn S. Murray +2
Acoustic telemetry data plays a vital role in understanding the behaviour and movement of aquatic animals. However, these datasets, which often consist of millions of individual da…
Anomaly Detection in Power Generation Plants with Generative Adversarial Networks
Marcellin Atemkeng, Toheeb Aduramomi Jimoh
Anomaly detection is a critical task that involves the identification of data points that deviate from a predefined pattern, useful for fraud detection and related activities. Vari…
Label Assisted Autoencoder for Anomaly Detection in Power Generation Plants
Marcellin Atemkeng, Victor Osanyindoro, Rockefeller Rockefeller +5
One of the critical factors that drive the economic development of a country and guarantee the sustainability of its industries is the constant availability of electricity. This is…
Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images
Yusuf Brima, Marcellin Atemkeng
Deep learning shows promise for medical image analysis but lacks interpretability, hindering adoption in healthcare. Attribution techniques that explain model reasoning may increas…
Predicting Fuel Consumption in Power Generation Plants using Machine Learning and Neural Networks
Gabin Maxime Nguegnang, Marcellin Atemkeng, Theophilus Ansah-Narh +2
The instability of power generation from national grids has led industries (e.g., telecommunication) to rely on plant generators to run their businesses. However, these secondary g…