6 papers · 1 filter
Unmixing ATR-μFTIR spectroscopic images of cross-sections of historical oil paintings
Shivam Pande, Nicolas Nadisic, Francisco Mederos-Henry +1
Spectroscopic imaging (SI) has become central to heritage science because it enables non-invasive, spatially resolved characterisation of materials in artefacts. In particular, att…
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…
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…
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…
Unfolding ADMM for Enhanced Subspace Clustering of Hyperspectral Images
Xianlu Li, Nicolas Nadisic, Shaoguang Huang +1
Deep subspace clustering methods are now prominent in clustering, typically using fully connected networks and a self-representation loss function. However, these methods often str…
OsmLocator: locating overlapping scatter marks with a non-training generative perspective
Yuming Qiu, Aleksandra Pizurica, Qi Ming +1
Automated mark localization in scatter images, greatly helpful for discovering knowledge and understanding enormous document images and reasoning in visual question answering AI sy…