The exponential growth of biomedical data—from multi-modal medical images to high-throughput omics profiles—has intensified the need for unsupervised learning methods capable of extracting meaningful ...

This paper presents a unified and adaptively integrated framework for unsupervised image clustering that establishes a novel synergistic interaction between self-supervised representation learning, ...

K-means is comparatively simple and works well with large datasets, but it assumes clusters are circular/spherical in shape, so it can only find simple cluster geometries. Data clustering is the ...