Browsing Institute of New Imaging Technologies (INIT) by Keyword "topic models"
Now showing items 1-2 of 2
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Hyperspectral Unmixing Based on Dual-Depth Sparse Probabilistic Latent Semantic Analysis
IEEE (2018-06)This paper presents a novel approach for spectral unmixing of remotely sensed hyperspectral data. It exploits probabilistic latent topics in order to take advantage of the semantics pervading the latent topic space when ... -
Sentinel-2 and Sentinel-3 Intersensor Vegetation Estimation via Constrained Topic Modeling
IEEE (2019-03)This letter presents a novel intersensor vegetation estimation framework, which aims at combining Sentinel-2 (S2) spatial resolution with Sentinel-3 (S3) spectral characteristics in order to generate fused vegetation maps. ...