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Found 4 papers, 2 papers with code
Deep Learning Hyperspectral Pansharpening on large scale PRISMA dataset
Second, we adapted several state of the art approaches based on deep learning to fit PRISMA hyperspectral data and then assessed, quantitatively and qualitatively, the performance in this new scenario.
A deep scalable neural architecture for soil properties estimation from spectral information
In this paper we propose an adaptive deep neural architecture for the prediction of multiple soil characteristics from the analysis of hyperspectral signatures.
Semi-supervised cross-lingual speech emotion recognition
Performance in Speech Emotion Recognition (SER) on a single language has increased greatly in the last few years thanks to the use of deep learning techniques.
Unsupervised Segmentation of Hyperspectral Remote Sensing Images with Superpixels
In this paper, we propose an unsupervised method for hyperspectral remote sensing image segmentation.
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