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Communication Dans Un Congrès Année : 2016

DEEP LEARNING APPROACH FOR REMOTE SENSING IMAGE ANALYSIS

Résumé

The paper explores how multimedia approaches used in image understanding tasks could be adapted for remote sensing image analysis. In a first step, we show on 3 channels color images through the UC Merced Land Use Dataset how Deep Learning approach provides a significant performance increase compared to Bag of VisualWords approach. In a second step, we propose an extension of deep learning scheme to deal with hyperspectral data. The proposed scheme is based on a 3D architecture which jointly processes spectral and spatial information.
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Amina Ben Hamida, A Benoit, Patrick Lambert, Chokri Ben-Amar. DEEP LEARNING APPROACH FOR REMOTE SENSING IMAGE ANALYSIS. Big Data from Space (BiDS'16), Mar 2016, Santa Cruz de Tenerife, Spain. pp.133, ⟨10.2788/854791⟩. ⟨hal-01370161⟩
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