A Gaussian Process Regression Approach for Fusion of Remote Sensing Images for Oil Spill Segmentation

doi 10.23919/icif.2018.8455304
Full Text
Abstract

Available in full text

Date
Authors
Publisher

IEEE

Related search

Parsimonious Gaussian Process Models for the Classification of Hyperspectral Remote Sensing Images

IEEE Geoscience and Remote Sensing Letters
Electronic EngineeringElectricalEngineering GeologyGeotechnical Engineering
2015English

Oil-Spill Pollution Remote Sensing by Synthetic Aperture Radar

2014English

Gaussian Process Regression for Geometry Optimization

Journal of Chemical Physics
MedicineTheoretical ChemistryAstronomyPhysicsPhysical
2018English

A Simulated Annealing Band Selection Approach for High-Dimensional Remote Sensing Images

2010English

Developing Integrated Remote Sensing and GIS Procedures for Oil Spill Monitoring on the Libyan Coast

2013English

Linking Gaussian Process Regression With Data-Driven Manifold Embeddings for Nonlinear Data Fusion

Interface Focus
BiochemistryBiophysicsBiomaterialsBioengineeringBiotechnologyBiomedical Engineering
2019English

Flooding and Oil Spill Disaster Relief Using Sentinel of Remote Sensing Satellite Data

International Journal of Advanced Computer Science and Applications
Computer Science
2019English

System for Automatic Registration of Remote Sensing Images

English

The Fusion of Remote Sensing Images Based on Lifting Wavelet Transformation

Computer and Information Science
2009English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy