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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 401–425 of 518 papers

TitleStatusHype
Challenges and Solutions for Utilizing Earth Observations in the "Big Data" era—0
Challenges in data-based geospatial modeling for environmental research and practice—0
Changer: Feature Interaction is What You Need for Change Detection—0
Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks—0
Class Attention Network for Semantic Segmentation of Remote Sensing Images—0
Cloud Removal in Remote Sensing Using Sequential-Based Diffusion Models—0
Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study—0
Cloud Removal with Fusion of High Resolution Optical and SAR Images Using Generative Adversarial Networks—0
SepHRNet: Generating High-Resolution Crop Maps from Remote Sensing imagery using HRNet with Separable Convolution—0
Serving economic prosperity: economic impact assessments (EIA) on Earth observation-based services and tools by SERVIR—0
Compressive Hyperspectral Imaging Using Progressive Total Variation—0
Confidence Estimation in Unsupervised Deep Change Vector Analysis—0
Context-Aware Change Detection With Semi-Supervised Learning—0
Continual Barlow Twins: continual self-supervised learning for remote sensing semantic segmentation—0
Short-Term Power Demand Forecasting for Diverse Consumer Types to Enhance Grid Planning and Synchronisation—0
Covariance Symmetries Classification in Multitemporal/Multipass PolSAR Images—0
Simulated annealing based heuristic for multiple agile satellites scheduling under cloud coverage uncertainty—0
Cross-Geography Generalization of Machine Learning Methods for Classification of Flooded Regions in Aerial Images—0
Understanding the impacts of crop diversification in the context of climate change: a machine learning approach—0
Cross-sensor self-supervised training and alignment for remote sensing—0
Advancements in Image Resolution: Super-Resolution Algorithm for Enhanced EOS-06 OCM-3 Data—0
Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward—0
Data Augmentation in Earth Observation: A Diffusion Model Approach—0
Data-Centric Machine Learning for Earth Observation: Necessary and Sufficient Features—0
Better, Not Just More: Data-Centric Machine Learning for Earth Observation—0
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