838 citations · 1.1k across the 13 of their papers we have counts for
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SpectralEarth: Training Hyperspectral Foundation Models at Scale
Nassim Ait Ali Braham, Conrad M Albrecht, Julien Mairal +3
Foundation models have triggered a paradigm shift in computer vision and are increasingly being adopted in remote sensing, particularly for multispectral imagery. Yet, their potent…
Spatial and Spatial-Spectral Morphological Mamba for Hyperspectral Image Classification
Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Adil Mehmood Khan +6
Recent advancements in transformers, specifically self-attention mechanisms, have significantly improved hyperspectral image (HSI) classification. However, these models often suffe…
Assessing the Potential of PlanetScope Satellite Imagery to Estimate Particulate Matter Oxidative Potential
Ian Hough, Loïc Argentier, Ziyang Jiang +6
Oxidative potential (OP), which measures particulate matter's (PM) capacity to induce oxidative stress in the lungs, is increasingly recognized as an indicator of PM toxicity. Sinc…
Hyperspectral Pansharpening: Critical Review, Tools and Future Perspectives
Matteo Ciotola, Giuseppe Guarino, Gemine Vivone +4
Hyperspectral pansharpening consists of fusing a high-resolution panchromatic band and a low-resolution hyperspectral image to obtain a new image with high resolution in both the s…
SpectralMamba: Efficient Mamba for Hyperspectral Image Classification
Jing Yao, Danfeng Hong, Chenyu Li +1
Recurrent neural networks and Transformers have recently dominated most applications in hyperspectral (HS) imaging, owing to their capability to capture long-range dependencies fro…
Low-Rank Representations Meets Deep Unfolding: A Generalized and Interpretable Network for Hyperspectral Anomaly Detection
Chenyu Li, Bing Zhang, Danfeng Hong +2
Current hyperspectral anomaly detection (HAD) benchmark datasets suffer from low resolution, simple background, and small size of the detection data. These factors also limit the p…