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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 276–300 of 518 papers

TitleStatusHype
GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing—0
A novel fusion of Sentinel-1 and Sentinel-2 with climate data for crop phenology estimation using Machine Learning—0
Statistical Learning for End-to-End Simulations—0
Generating Synthetic Oracle Datasets to Analyze Noise Impact: A Study on Building Function Classification Using Tweets—0
Generative Adversarial Training for Weakly Supervised Cloud Matting—0
Super-Resolution of PROBA-V Images Using Convolutional Neural Networks—0
Synergistic Integration of Optical and Microwave Satellite Data for Crop Yield Estimation—0
GeoLLM-Engine: A Realistic Environment for Building Geospatial Copilots—0
Geometric Correction and Mosaic Generation of Geo High Resolution Camera Images—0
GEOSCAN: Global Earth Observation using Swarm of Coordinated Autonomous Nanosats—0
Geospatial Foundation Models to Enable Progress on Sustainable Development Goals—0
A Cycle GAN Approach for Heterogeneous Domain Adaptation in Land Use Classification—0
Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space—0
Global High Categorical Resolution Land Cover Mapping via Weak Supervision—0
Gradient-based Automatic Look-Up Table Generator for Atmospheric Radiative Transfer Models—0
A Novel Full-Polarization SAR Images Ship Detector Based on the Scattering Mechanisms and the Wave Polarization Anisotropy—0
SyntEO: Synthetic Data Set Generation for Earth Observation and Deep Learning -- Demonstrated for Offshore Wind Farm Detection—0
Tensor Representation and Manifold Learning Methods for Remote Sensing Images—0
TerraMesh: A Planetary Mosaic of Multimodal Earth Observation Data—0
High-Resolution Satellite Imagery for Modeling the Impact of Aridification on Crop Production—0
Multitask Learning for Large-scale Semantic Change Detection—0
How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning—0
How Does the Spatial Distribution of Pre-training Data Affect Geospatial Foundation Models?—0
How Effective is Pre-training of Large Masked Autoencoders for Downstream Earth Observation Tasks?—0
TerraMind: Large-Scale Generative Multimodality for Earth Observation—0
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