Generating pre-harvest crop maps by applying convolutional neural network on multi-temporal Sentinel-1 data
Pre-harvest crop mapping, the fundamental requirement for many of the crop management
decisions, continues to be challenging either due to cloud cover in satellite images or due to …
decisions, continues to be challenging either due to cloud cover in satellite images or due to …
Multi-task hybrid spectral–spatial temporal convolution networks for classification of agricultural crop types and growth stages using drone-borne hyperspectral and …
B Chaudhury, AS Sahadevan… - Journal of Applied …, 2023 - spiedigitallibrary.org
Accurate crop type and crop growth stage maps are essential for agricultural monitoring and
ensuring food security. A wide variety of airborne and spaceborne sensors now provide high …
ensuring food security. A wide variety of airborne and spaceborne sensors now provide high …
Self-attention generative adversarial networks for times series VHR multispectral image generation
F Chaabane, S Réjichi, F Tupin - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Recently classical deep learning approaches are commonly used to perform spatial and
temporal classification especially for Very High Resolution (VHR) images. They learn from …
temporal classification especially for Very High Resolution (VHR) images. They learn from …
Transformation of multispectral data to quasi-hyperspectral data using convolutional neural network regression
Hyperspectral (HS) data are proven to be more resourceful compared to multispectral (MS)
data for object detection, classification, and several other applications. However, absence of …
data for object detection, classification, and several other applications. However, absence of …
Comparison between multitemporal graph based classical learning and LSTM model classifications for sits analysis
F Chaabane, S Réjichi, F Tupin - IGARSS 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
Very High Resolution (VHR) multispectral Satellite Image Time Series (SITS) enables the
production of temporal land cover maps, thanks to high spatial, temporal and spectral …
production of temporal land cover maps, thanks to high spatial, temporal and spectral …
Mutual Information based Spectrally Segmented Stacked Autoencoder Approach for Spectral-Spatial Classification of Land Use Land Cover Using Hyperspectral Data
Hyperspectral (HS) data comprises of continuous spectral responses of hundreds of narrow
spectral bands with very fine spectral resolution, which offers feature identification and …
spectral bands with very fine spectral resolution, which offers feature identification and …