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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 101–150 of 518 papers

TitleStatusHype
Scale Aware Adaptation for Land-Cover Classification in Remote Sensing ImageryCode1
Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover ClassificationCode1
Lightweight Temporal Self-Attention for Classifying Satellite Image Time SeriesCode1
Integrating Earth Observation Data into Causal Inference: Challenges and OpportunitiesCode1
Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity PredictionCode1
SenPa-MAE: Sensor Parameter Aware Masked Autoencoder for Multi-Satellite Self-Supervised PretrainingCode1
HTD-Mamba: Efficient Hyperspectral Target Detection with Pyramid State Space ModelCode1
Accounting for Input Noise in Gaussian Process Parameter RetrievalCode1
Crop Classification under Varying Cloud Cover with Neural Ordinary Differential EquationsCode1
Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical MapsCode1
Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial ImagesCode1
Local Window Attention Transformer for Polarimetric SAR Image ClassificationCode1
Hephaestus: A large scale multitask dataset towards InSAR understandingCode1
Geo-Tiles for Semantic Segmentation of Earth Observation ImageryCode1
HighRes-net: Multi-Frame Super-Resolution by Recursive FusionCode1
Learning a Cross-modality Anomaly Detector for Remote Sensing ImageryCode1
GeoLangBind: Unifying Earth Observation with Agglomerative Vision-Language Foundation ModelsCode1
Fuzzy clustering for the within-season estimation of cotton phenologyCode1
GeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K ResolutionCode1
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite ImageryCode1
Unsupervised Change Detection in Multi-temporal VHR Images Based on Deep Kernel PCA Convolutional Mapping NetworkCode1
Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing ImageryCode1
FarSeg++: Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing ImageryCode1
FLAIR #2: textural and temporal information for semantic segmentation from multi-source optical imageryCode1
Exchanging Dual Encoder-Decoder: A New Strategy for Change Detection with Semantic Guidance and Spatial LocalizationCode1
Ben-ge: Extending BigEarthNet with Geographical and Environmental DataCode1
Explainable Earth Surface Forecasting under Extreme EventsCode1
Deep Learning for Time Series Classification and Extrinsic Regression: A Current SurveyCode1
A Concise Tiling Strategy for Preserving Spatial Context in Earth Observation ImageryCode1
EarthPT: a time series foundation model for Earth ObservationCode1
Fusing VHR Post-disaster Aerial Imagery and LiDAR Data for Roof Classification in the CaribbeanCode1
High-Resolution Live Fuel Moisture Content (LFMC) Maps for Wildfire Risk from Multimodal Earth Observation DataCode1
FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature CompressionCode1
Deep Random Features for Scalable Interpolation of Spatiotemporal DataCode1
Deep Unsupervised Domain Adaptation for Time Series Classification: a BenchmarkCode1
EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impactsCode1
Multimodal learning-based inversion models for the space-time reconstruction of satellite-derived geophysical fieldsCode1
Generate Your Own Scotland: Satellite Image Generation Conditioned on MapsCode1
Disentangling Derivatives, Uncertainty and Error in Gaussian Process ModelsCode1
Deep learning approaches to Earth Observation change detection—0
Automatic Spatial Context-Sensitive Cloud/Cloud-Shadow Detection in Multi-Source Multi-Spectral Earth Observation Images: AutoCloud+—0
Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model Inversion—0
Automatic image annotation : the case of deforestation—0
Analyzing Poverty through Intra-Annual Time-Series: A Wavelet Transform Approach—0
Lossy Neural Compression for Geospatial Analytics: A Review—0
Deep Diffusion Models and Unsupervised Hyperspectral Unmixing for Realistic Abundance Map Synthesis—0
Automatic Census of Mussel Platforms Using Sentinel 2 Images—0
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing—0
Data-Driven Approach to assess and identify gaps in healthcare set up in South Asia—0
Automated National Urban Map Extraction—0
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