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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 251–275 of 518 papers

TitleStatusHype
Earth Observation Satellite Scheduling with Graph Neural Networks—0
Satellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping—0
Data-Centric Machine Learning for Earth Observation: Necessary and Sufficient Features—0
A novel fusion of Sentinel-1 and Sentinel-2 with climate data for crop phenology estimation using Machine Learning—0
Segment Using Just One Example—0
Specialized Change Detection using Segment Anything—0
Seg-CycleGAN : SAR-to-optical image translation guided by a downstream task—0
Estimating Earthquake Magnitude in Sentinel-1 Imagery via Ranking—0
Quanv4EO: Empowering Earth Observation by means of Quanvolutional Neural Networks—0
Increasing the Robustness of Model Predictions to Missing Sensors in Earth ObservationCode0
DeepExtremeCubes: Integrating Earth system spatio-temporal data for impact assessment of climate extremesCode0
Evaluating and Benchmarking Foundation Models for Earth Observation and Geospatial AI—0
Improving EO Foundation Models with Confidence Assessment for enhanced Semantic segmentationCode0
Low-power Ship Detection in Satellite Images Using Neuromorphic Hardware—0
A Late-Stage Bitemporal Feature Fusion Network for Semantic Change DetectionCode0
Data Augmentation in Earth Observation: A Diffusion Model Approach—0
Global High Categorical Resolution Land Cover Mapping via Weak Supervision—0
Responsible AI for Earth Observation—0
Towards Efficient Disaster Response via Cost-effective Unbiased Class Rate Estimation through Neyman Allocation Stratified Sampling Active Learning—0
Serving economic prosperity: economic impact assessments (EIA) on Earth observation-based services and tools by SERVIR—0
Eidos: Efficient, Imperceptible Adversarial 3D Point Clouds—0
Confidence Estimation in Unsupervised Deep Change Vector Analysis—0
Cross-sensor self-supervised training and alignment for remote sensing—0
Knowledge-aware Text-Image Retrieval for Remote Sensing Images—0
SatSwinMAE: Efficient Autoencoding for Multiscale Time-series Satellite Imagery—0
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