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Earth Observation

Earth Observation (EO) refers to the use of remote sensing technologies to monitor land, marine (seas, rivers, lakes) and atmosphere. Satellite-based EO relies on the use of satellite-mounted payloads to gather imaging data about the Earth’s characteristics. The images are then processed and analyzed in order to extract different types of information that can serve a very wide range of applications and industries.

Papers

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Showing 426–450 of 518 papers

TitleStatusHype
Scale Aware Adaptation for Land-Cover Classification in Remote Sensing ImageryCode1
Gradient-based Automatic Look-Up Table Generator for Atmospheric Radiative Transfer Models—0
Statistical Learning for End-to-End Simulations—0
Physics-Aware Gaussian Processes in Remote Sensing—0
Estimating Crop Primary Productivity with Sentinel-2 and Landsat 8 using Machine Learning Methods Trained with Radiative Transfer Simulations—0
Retrieval of aboveground crop nitrogen content with a hybrid machine learning method—0
Machine Learning Information Fusion in Earth Observation: A Comprehensive Review of Methods, Applications and Data Sources—0
Randomized kernels for large scale Earth observation applications—0
Crop Classification under Varying Cloud Cover with Neural Ordinary Differential EquationsCode1
Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing ImageryCode1
Living in the Physics and Machine Learning Interplay for Earth Observation—0
Unsupervised Self-training Algorithm Based on Deep Learning for Optical Aerial Images Change Detection—0
Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study—0
Interactive Learning for Semantic Segmentation in Earth ObservationCode0
Learning from Multimodal and Multitemporal Earth Observation Data for Building Damage Mapping—0
Deep Neural Networks for automatic extraction of features in time series satellite images—0
Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent NetworksCode1
Bottom-up mechanism and improved contract net protocol for the dynamic task planning of heterogeneous Earth observation resources—0
OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing—0
Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusionCode1
A Perspective on Gaussian Processes for Earth Observation—0
Learning Geocentric Object Pose in Oblique Monocular ImagesCode1
Lightweight Temporal Self-Attention for Classifying Satellite Image Time SeriesCode1
X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data—0
The color out of space: learning self-supervised representations for Earth Observation imageryCode1
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