Multitask Learning for SAR Ship Detection With Gaussian-Mask Joint Segmentation
Author:
Affiliation:
1. Department of Information Engineering, Shanghai Maritime University, Shanghai, China
2. Multimedia Communications and Signal Processing, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shanghai Municipality
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10225492.pdf?arnumber=10225492
Reference59 articles.
1. Imbalanced Learning-Based Automatic SAR Images Change Detection by Morphologically Supervised PCA-Net
2. SAR Image Despeckling by the Use of Variational Methods With Adaptive Nonlocal Functionals
3. Noncircularity parameters and their potential in ship detection from high resolution SAR imagery
4. Learning Deep Features for Discriminative Localization
5. Ship detection in polarimetric SAR images via variational Bayesian inference;marino;Proc IEEE Int Geosci Remote Sens Symp (IGARSS),2010
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