activity
20242026
collaborators

14 papers

cs.ET2026

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…

eess.IV2026

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…

cs.LG2026

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…

cs.LG2026

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.…

cs.CV2026

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…

cs.AI2026

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…