Improvement of Spatial Localization Accuracy in Learning-Based Patch Matching Using Anisotropic Fractal Brownian Motion Data
Author:
Affiliation:
1. National Aerospace University,Kharkov,Ukraine,61070
2. University of Rennes,Lannion Cedex,France,22305
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9883023/9883024/09883816.pdf?arnumber=9883816
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1. DeepMatching: Hierarchical Deformable Dense Matching
2. Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images
3. U-Net: Convolutional Networks for Biomedical Image Segmentation;ronneberger;Cham,2015
4. Exhaustive Search of Correspondences between Multimodal Remote Sensing Images Using Convolutional Neural Network
5. Comparison of learning-based and maximum-likelihood estimators of image noise variance for real-life and synthetic anisotropic textures
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