Semantic segmentation of remote sensing ship image via a convolutional neural networks model-Reference-Cited by-同舟云学术

Semantic segmentation of remote sensing ship image via a convolutional neural networks model

Published:2019-04-02 Issue:6 Volume:13 Page:1016-1022
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Wang Wenxiu¹²³,Fu Yutian¹²,Dong Feng¹²,Li Feng¹²³

Affiliation:

1. Department 9, CAS Key Laboratory of Infrared System Detection and Imaging TechnologyShanghai Institute of Technical PhysicsShanghai200083People's Republic of China

2. Department 9Shanghai Institute of Technical Physics of CASShanghai200083People's Republic of China

3. Department 9University of Chinese Academy of SciencesBeijing100049People's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2018.5914

Reference30 articles.

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2. 2009 Visual Analytics for Homeland Defense and Security. International Society for Optics and Photonics Orlando FL M. Riveiro G. Falkman T. Ziemke VISAD: an interactive and visual analytical tool for the detection of behavioral anomalies in maritime traffic data 734607

3. Semi‐supervised vision‐based maritime surveillance system using fused visual attention maps;Makantasis K.;Multimedia Tools Appl.,2016

4. Contextual region‐based convolutional neural network with multilayer fusion for SAR ship detection;Kang M.;Remote Sens.,2017

5. Automatic Ship Classification from Optical Aerial Images with Convolutional Neural Networks

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