Time Series Land Cover Challenge: a Deep Learning Perspective

Medium post

Abstract

Time Series Satellite Imagery is the addition of a temporal dimension to Satellite Imagery. We see in this post how a 10-bands satellite imagery takes benefit from this temporal dimension by using combination of unimodal and multimodel neural networks architecture used in the context of sequential data.

Publication
Time Series Land Cover Challenge: a Deep Learning Perspective
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Thomas Di Martino
PhD Student in AI & Remote Sensing

My research interests include deep learning technologies, automatic feature extraction and computer vision, all of them applied to Remote Sensing problematics, more precisely to Synthetic Aperture Radar (SAR) acquisitions.

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