Missing information reconstruction of remote sensing data: A technical review
Because of sensor malfunction and poor atmospheric conditions, there is usually a great
deal of missing information in optical remote sensing data, which reduces the usage rate …
deal of missing information in optical remote sensing data, which reduces the usage rate …
Remote sensing image mosaicking: Achievements and challenges
Remote Sensing Image Mosaicking: Achievements and Challenges Page 1 8 0274-6638/19©2019IEEE
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE DECEMBER 2019 Image …
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE DECEMBER 2019 Image …
[HTML][HTML] Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion
Optical remote sensing imagery is at the core of many Earth observation activities. The
regular, consistent and global-scale nature of the satellite data is exploited in many …
regular, consistent and global-scale nature of the satellite data is exploited in many …
Missing data reconstruction in remote sensing image with a unified spatial–temporal–spectral deep convolutional neural network
Because of the internal malfunction of satellite sensors and poor atmospheric conditions
such as thick cloud, the acquired remote sensing data often suffer from missing information …
such as thick cloud, the acquired remote sensing data often suffer from missing information …
A survey of intelligent transmission line inspection based on unmanned aerial vehicle
Y Luo, X Yu, D Yang, B Zhou - Artificial Intelligence Review, 2023 - Springer
With the development of the new generation of information technology, artificial intelligence,
cloud computing and big data are gradually becoming powerful engines of the smart grid. In …
cloud computing and big data are gradually becoming powerful engines of the smart grid. In …
Prediction of soil organic carbon and the C: N ratio on a national scale using machine learning and satellite data: A comparison between Sentinel-2, Sentinel-3 and …
T Zhou, Y Geng, C Ji, X Xu, H Wang, J Pan… - Science of the Total …, 2021 - Elsevier
Soil organic carbon (SOC) and soil carbon-to-nitrogen ratio (C: N) are the main indicators of
soil quality and health and play an important role in maintaining soil quality. Together with …
soil quality and health and play an important role in maintaining soil quality. Together with …
Evolving fusion-based visibility restoration model for hazy remote sensing images using dynamic differential evolution
Remote sensing images taken during poor environmental conditions are degraded by the
scattering of atmospheric particles, which affects the performance of many imaging systems …
scattering of atmospheric particles, which affects the performance of many imaging systems …
Multi-feature combined cloud and cloud shadow detection in GaoFen-1 wide field of view imagery
The wide field of view (WFV) imaging system onboard the Chinese GaoFen-1 (GF-1) optical
satellite has a 16-m resolution and four-day revisit cycle for large-scale Earth observation …
satellite has a 16-m resolution and four-day revisit cycle for large-scale Earth observation …
Skin lesion segmentation from dermoscopic images using convolutional neural network
Clinical treatment of skin lesion is primarily dependent on timely detection and delimitation
of lesion boundaries for accurate cancerous region localization. Prevalence of skin cancer is …
of lesion boundaries for accurate cancerous region localization. Prevalence of skin cancer is …
Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning
Thick cloud and its shadow severely reduce the data usability of optical satellite remote
sensing data. Although many approaches have been presented for cloud and cloud shadow …
sensing data. Although many approaches have been presented for cloud and cloud shadow …