5 papers
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…
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…
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…
A Systematic Review of Low-Rank and Local Low-Rank Matrix Approximation in Big Data Medical Imaging
Sisipho Hamlomo, Marcellin Atemkeng, Yusuf Brima +2
The large volume and complexity of medical imaging datasets are bottlenecks for storage, transmission, and processing. To tackle these challenges, the application of low-rank matri…
Ethics of Software Programming with Generative AI: Is Programming without Generative AI always radical?
Marcellin Atemkeng, Sisipho Hamlomo, Brian Welman +3
This paper provides a comprehensive analysis of Generative AI (GenAI) potential to revolutionise software coding through increased efficiency and reduced time span for writing code…