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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 126–150 of 518 papers

TitleStatusHype
Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusionCode1
Lightweight Temporal Self-Attention for Classifying Satellite Image Time SeriesCode1
Learning Geocentric Object Pose in Oblique Monocular ImagesCode1
The color out of space: learning self-supervised representations for Earth Observation imageryCode1
Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V images for Cloud DetectionCode1
Accounting for Input Noise in Gaussian Process Parameter RetrievalCode1
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite ImageryCode1
HighRes-net: Multi-Frame Super-Resolution by Recursive FusionCode1
Unsupervised Change Detection in Multi-temporal VHR Images Based on Deep Kernel PCA Convolutional Mapping NetworkCode1
Cloud Removal in Satellite Images Using Spatiotemporal Generative NetworksCode1
Object Detection in Optical Remote Sensing Images: A Survey and A New BenchmarkCode1
Proximity Forest: An effective and scalable distance-based classifier for time seriesCode1
DOTA: A Large-scale Dataset for Object Detection in Aerial ImagesCode1
EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover ClassificationCode1
SCORE: Scene Context Matters in Open-Vocabulary Remote Sensing Instance SegmentationCode0
TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis—0
Towards Scalable and Generalizable Earth Observation Data Mining via Foundation Model Composition—0
Spiking Neural Networks for SAR Interferometric Phase Unwrapping: A Theoretical Framework for Energy-Efficient Processing—0
Multi-Agent Reinforcement Learning for Autonomous Multi-Satellite Earth Observation: A Realistic Case Study—0
Scaling-Up the Pretraining of the Earth Observation Foundation Model PhilEO to the MajorTOM DatasetCode0
Deep Diffusion Models and Unsupervised Hyperspectral Unmixing for Realistic Abundance Map Synthesis—0
Atomizer: Generalizing to new modalities by breaking satellite images down to a set of scalars—0
CanadaFireSat: Toward high-resolution wildfire forecasting with multiple modalities—0
FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping—0
Short-Term Power Demand Forecasting for Diverse Consumer Types to Enhance Grid Planning and Synchronisation—0
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