Open-world recognition in remote sensing: Concepts, challenges, and opportunities
In recent years, remote sensing recognition technology has found extensive applications in
diverse fields, such as modern agriculture, forest management, urban planning, natural …
diverse fields, such as modern agriculture, forest management, urban planning, natural …
Some novel hybrid forecast methods based on picture fuzzy clustering for weather nowcasting from satellite image sequences
Weather nowcasting comprises the detailed description of the current weather along with
forecasts obtained by extrapolation for very short-range period of zero to six hours ahead. It …
forecasts obtained by extrapolation for very short-range period of zero to six hours ahead. It …
MSTCGAN: Multiscale time conditional generative adversarial network for long-term satellite image sequence prediction
Satellite image sequence prediction is a crucial and challenging task. Previous studies
leverage optical flow methods or existing deep learning methods on spatial–temporal …
leverage optical flow methods or existing deep learning methods on spatial–temporal …
Cloud masking and removal in remote sensing image time series
L Gómez-Chova, J Amorós-López… - Journal of Applied …, 2017 - spiedigitallibrary.org
Automatic cloud masking of Earth observation images is one of the first required steps in
optical remote sensing data processing since the operational use and product generation …
optical remote sensing data processing since the operational use and product generation …
Multi-modal spatio-temporal meteorological forecasting with deep neural network
Meteorological forecasting is a typical and fundamental problem in the remote sensing field.
Although many brilliant forecasting methods have been developed, long-term (a few days …
Although many brilliant forecasting methods have been developed, long-term (a few days …
Learning spatial-temporal consistency for satellite image sequence prediction
As an extremely challenging spatial–temporal sequence prediction task, satellite image
sequence prediction has various and significant applications in real-world scenarios …
sequence prediction has various and significant applications in real-world scenarios …
Mcsip net: Multichannel satellite image prediction via deep neural network
Satellite image prediction is important in weather nowcasting. In this article, we propose a
novel multichannel satellite image prediction network (MCSIP Net) for predicting satellite …
novel multichannel satellite image prediction network (MCSIP Net) for predicting satellite …
TrackInk: An IoT-enabled real-time object tracking system in space
Nowadays, there is tremendous growth in the Internet of Things (IoT) applications in our
everyday lives. The proliferation of smart devices, sensors technology, and the Internet …
everyday lives. The proliferation of smart devices, sensors technology, and the Internet …
AF-SRNet: Quantitative Precipitation Forecasting Model Based on Attention Fusion Mechanism and Residual Spatiotemporal Feature Extraction
Reliable quantitative precipitation forecasting is essential to society. At present, quantitative
precipitation forecasting based on weather radar represents an urgently needed, yet rather …
precipitation forecasting based on weather radar represents an urgently needed, yet rather …
Toward a deep-learning-network-based convective weather initiation algorithm from the joint observations of Fengyun-4A geostationary satellite and radar for 0–1h …
F Sun, B Li, M Min, D Qin - IEEE Journal of Selected Topics in …, 2023 - ieeexplore.ieee.org
Nowcasting of convective weather is a challenging and significant task in operational
weather forecasting system. In this article, a new convolution recurrent neural network based …
weather forecasting system. In this article, a new convolution recurrent neural network based …