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DEEP LEARNING APPROACH FOR REMOTE SENSING IMAGE ANALYSIS

Abstract : 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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https://hal.archives-ouvertes.fr/hal-01370161
Contributor : Patrick Lambert Connect in order to contact the contributor
Submitted on : Thursday, September 22, 2016 - 10:05:14 AM
Last modification on : Friday, November 6, 2020 - 3:27:36 AM

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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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