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Semantic segmentation method and device for radar image and storage medium

A semantic segmentation and radar image technology, applied in the radar field, can solve the problem of low target recognition accuracy, achieve good segmentation effect, high recognition accuracy, and improve accuracy

Active Publication Date: 2021-05-28
北京理工大学前沿技术研究院 +1
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Problems solved by technology

[0004] Embodiments of the present application provide a semantic segmentation method, device, and storage medium for radar images, which are used to solve the following technical problems in the prior art: when performing semantic segmentation on radar images, the accuracy of target recognition is low

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[0032] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Those skilled in the art should understand that the embodiments described in the detailed description in this section are only some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments described in the specific implementation methods in this section, all other embodiments obtained by persons of ordinary skill in the art without creative work will not deviate from the technical principle of the application, so they should all fall into the to the scope of protection of this application.

[0033] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0034] figur...

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Abstract

The invention discloses a semantic segmentation method and device for a radar image and a storage medium. The semantic segmentation method comprises the steps of obtaining radar data; rendering the radar data to determine a radar image; and inputting the radar image into a pre-trained semantic segmentation neural network model to identify the biological target in the radar image, wherein the semantic segmentation neural network model is obtained based on training of a double-flow convolutional neural network model GSCNN. According to the embodiment of the invention, the semantic segmentation neural network model is obtained through the double-flow convolutional neural network model, accurate semantic segmentation of the radar image can be realized, a better segmentation effect is achieved, and the accuracy of target recognition is improved when the biological target in the radar image is recognized and extracted.

Description

technical field [0001] The present application relates to the field of radar technology, in particular to a method, device and storage medium for semantic segmentation of radar images. Background technique [0002] Radar plays an increasingly important role in national life and plays an important role in domestic ecological protection. The current active development in the field of machine learning provides convenient conditions for processing a large amount of complex radar image data, and has gradually become the mainstream method for radar image target recognition to distinguish different echoes in radar images. [0003] However, the previous research on radar image processing mostly stays on the image-level classification, and the research work on pixel-level segmentation is less, and has not achieved better segmentation performance, and the accuracy of target recognition is low. Contents of the invention [0004] Embodiments of the present application provide a seman...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/34G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V20/13G06V10/267G06V10/40G06N3/045G06F18/24Y02A90/10
Inventor 王锐王帅航崔铠毛华峰胡程
Owner 北京理工大学前沿技术研究院
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