3 papers
eess.IV2026
Polyhedral Unmixing: Bridging Semantic Segmentation with Hyperspectral Unmixing via Polyhedral-Cone Partitioning
Antoine Bottenmuller, Etienne Decencière, Petr Dokládal
Semantic segmentation and hyperspectral unmixing are two central problems in spectral image analysis. The former assigns each pixel a discrete label corresponding to its material c…
cs.CV2026
Multi-Level Feature Fusion for Continual Learning in Visual Quality Inspection
Johannes C. Bauer, Paul Geng, Stephan Trattnig +2
Deep neural networks show great potential for automating various visual quality inspection tasks in manufacturing. However, their applicability is limited in more volatile scenario…
eess.IV2025
Euclidean Distance to Convex Polyhedra and Application to Class Representation in Spectral Images
Antoine Bottenmuller, Florent Magaud, Arnaud Demortière +2
With the aim of estimating the abundance map from observations only, linear unmixing approaches are not always suitable to spectral images, especially when the number of bands is t…