3 papers
cs.CV2025
Joint Superpixel and Self-Representation Learning for Scalable Hyperspectral Image Clustering
Xianlu Li, Nicolas Nadisic, Shaoguang Huang +1
Subspace clustering is a powerful unsupervised approach for hyperspectral image (HSI) analysis, but its high computational and memory costs limit scalability. Superpixel segmentati…
cs.CV2025
Generalized Category Discovery in Hyperspectral Images via Prototype Subspace Modeling
Xianlu Li, Nicolas Nadisic, Shaoguang Huang +1
Generalized category discovery~(GCD) seeks to jointly identify both known and novel categories in unlabeled data. While prior works have mainly focused on RGB images, their assumpt…
cs.CV2025
Scalable Context-Preserving Model-Aware Deep Clustering for Hyperspectral Images
Xianlu Li, Nicolas Nadisic, Shaoguang Huang +2
Subspace clustering has become widely adopted for the unsupervised analysis of hyperspectral images (HSIs). Recent model-aware deep subspace clustering methods often use a two-stag…