Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

SAR image ship target detection method and system based on training from scratch

A target detection and ship technology, applied in the field of target detection and radar remote sensing, can solve the problems of incompatibility between the model and the target, large amount of calculation, large model size, etc.

Pending Publication Date: 2021-09-21
中国人民解放军海军航空大学航空作战勤务学院
View PDF5 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, if these algorithms are directly applied to SAR images, there will be problems that the model does not adapt to the target, the model size is large, and the amount of calculation is large.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • SAR image ship target detection method and system based on training from scratch
  • SAR image ship target detection method and system based on training from scratch
  • SAR image ship target detection method and system based on training from scratch

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053]The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0054] The purpose of the present invention is to provide a SAR image ship target detection method and system based on training from scratch, so as to reduce the detection model size and target detection time while improving the target detection accuracy.

[0055] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompa...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to an SAR image ship target detection method and system based on training from scratch According to the SAR image ship target detection method based on training from scratch, a ship target detection model comprising a backbone network SAR-SDB and a front-end network SAR-SDF is designed for overcoming the defects of a deep learning detection algorithm used for SAR images so as to be used for achieving accurate detection of a target. The backbone network SAR-SDB has strong feature expression ability, reduces the number of channels, reduces the model size and calculation amount, and avoids the problem of overfitting. By adopting the front-end network SAR-SDF, the accuracy of target classification and positioning can be improved, so that the size of a target detection model is reduced and the target detection time is shortened while the detection accuracy is improved.

Description

technical field [0001] The invention relates to the technical fields of target detection and radar remote sensing, in particular to a SAR image ship target detection method and system based on ab initio training. Background technique [0002] Synthetic Aperture Radar (SAR) has been widely used in surface ship target surveillance due to its all-day and all-weather working characteristics. The traditional method is based on Constant False-Alarm Rate (CFAR). CFAR needs to first estimate the distribution model of SAR image pixels. When the SAR image background is complex, the model estimation will be inaccurate, resulting in a large number of false alarms and omissions. police. Since deep learning showed great advantages in the field of target detection in 2014, many researchers (Li J, Qu C, Shao J. Ship detection in SAR images based on an improved faster R-CNN[C]. 2017SAR in Big Data Era:Models , Methods and Applications (BIGSARDATA). IEEE, 2017.) applied them to ship target ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/04G06N3/08G06F18/241G06F18/214
Inventor 李健伟徐从安何明苏航周伟吴俊峰孙炜玮
Owner 中国人民解放军海军航空大学航空作战勤务学院
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com