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

Ground object target detection method and system for remote sensing image

A technology of remote sensing image and target detection, which is applied in the field of computer vision to improve the multi-scale target detection problem, improve the detection effect, and improve the detection accuracy

Active Publication Date: 2020-09-04
AEROSPACE INFORMATION RES INST CAS
View PDF5 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Most common algorithms fuse features of different scales to enhance the information around small objects, ignoring the lack of information due to size differences

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
  • Ground object target detection method and system for remote sensing image
  • Ground object target detection method and system for remote sensing image
  • Ground object target detection method and system for remote sensing image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0056] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0057] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. 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.

[0058] The invention provides a method for detecting ground object objects in remote sensing images, such as figure 1 shown, including:

[0059] 101. Input the remote sensing image to...

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 a remote sensing image ground object target detection method and system, and the method comprises the steps: inputting a to-be-detected remote sensing image to a pre-trained detection network, and obtaining an initial ground object target detection result, outputted by the pre-trained detection network, of the to-be-detected remote sensing image; screening the initial ground object target detection result by using a non-maximum suppression algorithm to obtain a final ground object target detection result of the to-be-detected remote sensing image; according to the technical scheme provided by the invention, the problem of small object detection in a complex remote sensing scene is effectively solved, attention is dynamically distributed to objects of different scales, and an effective technology is provided for subsequent computer vision tasks including but not limited to remote sensing image target detection.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a method and system for detecting ground object objects in remote sensing images. Background technique [0002] With the development of deep learning, convolutional neural networks have made breakthroughs in the field of image classification and recognition of natural scenes. Compared with natural scenes, optical satellite remote sensing images are large in size, complex in background, and contain a large number of objects. The target size is small, and in some scenes, small targets are densely clustered together and it is difficult to distinguish them; in addition, there are also phenomena such as target rotation and affine, as well as the influence of clouds, sea ripples, shadows, lighting and shooting angles; in practical applications, the detection speed requirements Also higher. This makes deep learning methods in computer vision not directly applicable to the field of remote...

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
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V20/13G06N3/045G06F18/24
Inventor 孙显王佩瑾刁文辉张义闫志远冯瑛超马益杭许滔
Owner AEROSPACE INFORMATION RES INST CAS
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