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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 226–250 of 518 papers

TitleStatusHype
MetaSegNet: Metadata-collaborative Vision-Language Representation Learning for Semantic Segmentation of Remote Sensing Images—0
Mapping Housing Stock Characteristics from Drone Images for Climate Resilience in the Caribbean—0
SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation ImageryCode3
Deep Unsupervised Domain Adaptation for Time Series Classification: a BenchmarkCode1
SeasFire as a Multivariate Earth System Datacube for Wildfire DynamicsCode0
Better, Not Just More: Data-Centric Machine Learning for Earth Observation—0
Artificial Neural Network for Estimation of Physical Parameters of Sea Water using LiDAR Waveforms—0
SICKLE: A Multi-Sensor Satellite Imagery Dataset Annotated with Multiple Key Cropping ParametersCode1
Creating and Leveraging a Synthetic Dataset of Cloud Optical Thickness Measures for Cloud Detection in MSICode0
Q-Seg: Quantum Annealing-Based Unsupervised Image SegmentationCode1
Multimodal deep learning for mapping forest dominant height by fusing GEDI with earth observation data—0
Exchanging Dual Encoder-Decoder: A New Strategy for Change Detection with Semantic Guidance and Spatial LocalizationCode1
Low-Precision Floating-Point for Efficient On-Board Deep Neural Network Processing—0
Challenges in data-based geospatial modeling for environmental research and practice—0
Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection—0
Explainable AI for Earth Observation: Current Methods, Open Challenges, and Opportunities—0
Standardized Analysis Ready (STAR) data cube for high-resolution Flood mapping using Sentinel-1 data—0
Supervised domain adaptation for building extraction from off-nadir aerial images—0
Mapping of Land Use and Land Cover (LULC) using EuroSAT and Transfer LearningCode0
Forest aboveground biomass estimation using GEDI and earth observation data through attention-based deep learning—0
There Are No Data Like More Data- Datasets for Deep Learning in Earth Observation—0
Foundation Models for Generalist Geospatial Artificial IntelligenceCode0
Multimodal Transformer Using Cross-Channel attention for Object Detection in Remote Sensing ImagesCode1
Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical MapsCode1
Transformer-based Multimodal Change Detection with Multitask Consistency ConstraintsCode1
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