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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 401–450 of 518 papers

TitleStatusHype
Practical IMT and EESS Spectrum Sharing in the 7 to 8 GHz Band—0
Predicting Internet Connectivity in Schools: A Feasibility Study Leveraging Multi-modal Data and Location Encoders in Low-Resource Settings—0
Towards Scalable and Generalizable Earth Observation Data Mining via Foundation Model Composition—0
Pre-processing training data improves accuracy and generalisability of convolutional neural network based landscape semantic segmentation—0
A Geospatial Approach to Predicting Desert Locust Breeding Grounds in Africa—0
Probabilistic Machine Learning for Noisy Labels in Earth Observation—0
Providentia -- A Large-Scale Sensor System for the Assistance of Autonomous Vehicles and Its Evaluation—0
Towards seamless multi-view scene analysis from satellite to street-level—0
A generic self-supervised learning (SSL) framework for representation learning from spectra-spatial feature of unlabeled remote sensing imagery—0
Towards Sustainable Satellite Edge Computing—0
QSpeckleFilter: a Quantum Machine Learning approach for SAR speckle filtering—0
Quantum algorithms applied to satellite mission planning for Earth observation—0
Quanv4EO: Empowering Earth Observation by means of Quanvolutional Neural Networks—0
Quick unsupervised hyperspectral dimensionality reduction for earth observation: a comparison—0
Randomized kernels for large scale Earth observation applications—0
Rapid Adaptation of Earth Observation Foundation Models for Segmentation—0
Reducing Uncertainties of a Chained Hydrologic-hydraulic Model to Improve Flood Forecasting Using Multi-source Earth Observation Data—0
Regression in EO: Are VLMs Up to the Challenge?—0
A General Purpose Neural Architecture for Geospatial Systems—0
Training-free AI for Earth Observation Change Detection using Physics Aware Neuromorphic Networks—0
Transfer Learning for Segmenting Dimensionally-Reduced Hyperspectral Images—0
REO-VLM: Transforming VLM to Meet Regression Challenges in Earth Observation—0
Responsible AI for Earth Observation—0
Retrieval of aboveground crop nitrogen content with a hybrid machine learning method—0
RingMoE: Mixture-of-Modality-Experts Multi-Modal Foundation Models for Universal Remote Sensing Image Interpretation—0
Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields—0
Robust Semantic Segmentation By Dense Fusion Network On Blurred VHR Remote Sensing Images—0
RS-DGC: Exploring Neighborhood Statistics for Dynamic Gradient Compression on Remote Sensing Image Interpretation—0
SAAN: Similarity-aware attention flow network for change detection with VHR remote sensing images—0
Advancing Earth Observation: A Survey on AI-Powered Image Processing in Satellites—0
Advances in Fine Line-Of-Sight Control for Large Space Flexible Structures—0
SAR-to-RGB Translation with Latent Diffusion for Earth Observation—0
Satellite image classification with neural quantum kernels—0
Satellite Image Search in AgoraEO—0
Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery—0
Satellite-Net: Automatic Extraction of Land Cover Indicators from Satellite Imagery by Deep Learning—0
Satellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping—0
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation—0
Scalable Data Transmission Framework for Earth Observation Satellites with Channel Adaptation—0
Transition Is a Process: Pair-to-Video Change Detection Networks for Very High Resolution Remote Sensing Images—0
An energy-efficient learning solution for the Agile Earth Observation Satellite Scheduling Problem—0
Schedule Earth Observation satellites with Deep Reinforcement Learning—0
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change SegmentationCode0
GeoMultiTaskNet: remote sensing unsupervised domain adaptation using geographical coordinatesCode0
DeepExtremeCubes: Integrating Earth system spatio-temporal data for impact assessment of climate extremesCode0
A speckle filter for Sentinel-1 SAR Ground Range Detected data based on Residual Convolutional Neural NetworksCode0
Local Binary and Multiclass SVMs Trained on a Quantum AnnealerCode0
Get Your Embedding Space in Order: Domain-Adaptive Regression for Forest MonitoringCode0
SatDM: Synthesizing Realistic Satellite Image with Semantic Layout Conditioning using Diffusion ModelsCode0
DeepCL: Deep Change Feature Learning on Remote Sensing Images in the Metric SpaceCode0
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