Temporal convolutional neural network for the classification of satellite image time series
Latest remote sensing sensors are capable of acquiring high spatial and spectral Satellite
Image Time Series (SITS) of the world. These image series are a key component of …
Image Time Series (SITS) of the world. These image series are a key component of …
Lightweight temporal self-attention for classifying satellite images time series
VSF Garnot, L Landrieu - Advanced Analytics and Learning on Temporal …, 2020 - Springer
The increasing accessibility and precision of Earth observation satellite data offers
considerable opportunities for industrial and state actors alike. This calls however for …
considerable opportunities for industrial and state actors alike. This calls however for …
DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn
Abstract Nowadays, modern Earth Observation systems continuously generate huge
amounts of data. A notable example is represented by the Sentinel-2 mission, which …
amounts of data. A notable example is represented by the Sentinel-2 mission, which …
Channel attention-based temporal convolutional network for satellite image time series classification
Satellite image time series classification has become a research focus with the launch of
new remote sensing sensors capable of capturing images with high spatial, spectral, and …
new remote sensing sensors capable of capturing images with high spatial, spectral, and …
Land cover classification via multitemporal spatial data by deep recurrent neural networks
Nowadays, modern earth observation programs produce huge volumes of satellite images
time series that can be useful to monitor geographical areas through time. How to efficiently …
time series that can be useful to monitor geographical areas through time. How to efficiently …
Self-supervised pretraining of transformers for satellite image time series classification
Y Yuan, L Lin - IEEE Journal of Selected Topics in Applied …, 2020 - ieeexplore.ieee.org
Satellite image time series (SITS) classification is a major research topic in remote sensing
and is relevant for a wide range of applications. Deep learning approaches have been …
and is relevant for a wide range of applications. Deep learning approaches have been …
Multi-temporal land cover classification with long short-term memory neural networks
Land cover classification (LCC) is a central and wide field of research in earth observation
and has already put forth a variety of classification techniques. Many approaches are based …
and has already put forth a variety of classification techniques. Many approaches are based …
Satellite image time series classification with pixel-set encoders and temporal self-attention
Satellite image time series, bolstered by their growing availability, are at the forefront of an
extensive effort towards automated Earth monitoring by international institutions. In …
extensive effort towards automated Earth monitoring by international institutions. In …
Self-attention for raw optical satellite time series classification
The amount of available Earth observation data has increased dramatically in recent years.
Efficiently making use of the entire body of information is a current challenge in remote …
Efficiently making use of the entire body of information is a current challenge in remote …
[HTML][HTML] Time series remote sensing image classification framework using combination of deep learning and multiple classifiers system
Recently, time series image (TSI) has been reported to be an effective resource to mapping
fine land use/land cover (LULC), and deep learning, in particular, has been gaining growing …
fine land use/land cover (LULC), and deep learning, in particular, has been gaining growing …