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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 176–200 of 518 papers

TitleStatusHype
Cross-sensor self-supervised training and alignment for remote sensing—0
SARATR-X: Toward Building A Foundation Model for SAR Target RecognitionCode3
Knowledge-aware Text-Image Retrieval for Remote Sensing Images—0
MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation LearningCode2
SatSwinMAE: Efficient Autoencoding for Multiscale Time-series Satellite Imagery—0
Get Your Embedding Space in Order: Domain-Adaptive Regression for Forest MonitoringCode0
Cross-sensor super-resolution of irregularly sampled Sentinel-2 time seriesCode1
GeoLLM-Engine: A Realistic Environment for Building Geospatial Copilots—0
Equivariant Imaging for Self-supervised Hyperspectral Image Inpainting—0
Generalized Few-Shot Meets Remote Sensing: Discovering Novel Classes in Land Cover Mapping via Hybrid Semantic Segmentation FrameworkCode2
Detecting Out-Of-Distribution Earth Observation Images with Diffusion Models—0
Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial ImagesCode1
A Semantic Segmentation-guided Approach for Ground-to-Aerial Image MatchingCode1
A Concise Tiling Strategy for Preserving Spatial Context in Earth Observation ImageryCode1
Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation—0
Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite DataCode0
OmniSat: Self-Supervised Modality Fusion for Earth ObservationCode2
Onboard Processing of Hyperspectral Imagery: Deep Learning Advancements, Methodologies, Challenges, and Emerging Trends—0
Automated National Urban Map Extraction—0
Deep Learning for Satellite Image Time Series Analysis: A Review—0
Neural Embedding Compression For Efficient Multi-Task Earth Observation ModellingCode0
FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature CompressionCode1
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation—0
Neural Plasticity-Inspired Multimodal Foundation Model for Earth ObservationCode2
Assimilation of SWOT Altimetry and Sentinel-1 Flood Extent Observations for Flood Reanalysis -- A Proof-of-Concept—0
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