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Deep Learning for Satellite Image Time Series Analysis: A Review
Lynn Miller, Charlotte Pelletier, Geoffrey I. Webb
Earth observation (EO) satellite missions have been providing detailed images about the state of the Earth and its land cover for over 50 years. Long term missions, such as NASA's…
Generalized Classification of Satellite Image Time Series with Thermal Positional Encoding
Joachim Nyborg, Charlotte Pelletier, Ira Assent
Large-scale crop type classification is a task at the core of remote sensing efforts with applications of both economic and ecological importance. Current state-of-the-art deep lea…
TimeMatch: Unsupervised Cross-Region Adaptation by Temporal Shift Estimation
Joachim Nyborg, Charlotte Pelletier, Sébastien Lefèvre +1
The recent developments of deep learning models that capture complex temporal patterns of crop phenology have greatly advanced crop classification from Satellite Image Time Series…
Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series
Charlotte Pelletier, Geoffrey I. Webb, Francois Petitjean
New remote sensing sensors now acquire high spatial and spectral Satellite Image Time Series (SITS) of the world. These series of images are a key component of classification syste…