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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 376–400 of 518 papers

TitleStatusHype
Cross-Geography Generalization of Machine Learning Methods for Classification of Flooded Regions in Aerial Images—0
Advances in Fine Line-Of-Sight Control for Large Space Flexible Structures—0
EOD: The IEEE GRSS Earth Observation Database—0
High-Resolution Satellite Imagery for Modeling the Impact of Aridification on Crop Production—0
Changer: Feature Interaction is What You Need for Change Detection—0
Spotting Virus from Satellites: Modeling the Circulation of West Nile Virus Through Graph Neural Networks—0
Fast Fourier Convolution Based Remote Sensor Image Object Detection for Earth Observation—0
Learning crop type mapping from regional label proportions in large-scale SAR and optical imagery—0
Satellite Image Search in AgoraEO—0
Multimodal Crop Type Classification Fusing Multi-Spectral Satellite Time Series with Farmers Crop Rotations and Local Crop Distribution—0
Noise-Adaptive Intelligent Programmable Meta-Imager—0
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing—0
METER-ML: A Multi-Sensor Earth Observation Benchmark for Automated Methane Source Mapping—0
Multi-strip observation scheduling problem for ac-tive-imaging agile earth observation satellites—0
Three multi-objective memtic algorithms for observation scheduling problem of active-imaging AEOS—0
Large region targets observation scheduling by multiple satellites using resampling particle swarm optimization—0
Time Gated Convolutional Neural Networks for Crop Classification—0
MultiEarth 2022 -- The Champion Solution for the Matrix Completion Challenge via Multimodal Regression and Generation—0
Continual Barlow Twins: continual self-supervised learning for remote sensing semantic segmentation—0
Pest presence prediction using interpretable machine learning—0
Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites—0
Innovations in the field of on-board scheduling technologies—0
Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review—0
On the semantics of big Earth observation data for land classification—0
CroCo: Cross-Modal Contrastive learning for localization of Earth Observation dataCode0
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