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A Method for Describing Sunspot Groups in Full Sun Surface Images

A technology in sunspots and images, which is applied in still image data retrieval, still image data indexing, still image data clustering/classification, etc., can solve problems such as sunspot group description not involved, and achieve the effect of improving the quality of description

Active Publication Date: 2022-06-07
KUNMING UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, image description technology is generally used in some daily image scenes, but the research on sunspot group description has not covered

Method used

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  • A Method for Describing Sunspot Groups in Full Sun Surface Images
  • A Method for Describing Sunspot Groups in Full Sun Surface Images
  • A Method for Describing Sunspot Groups in Full Sun Surface Images

Examples

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Embodiment 1

[0021] Example 1: as Figure 1-4 As shown, a method for describing sunspot groups in an all-solar image, the steps are as follows:

[0022] Step 1: Sunspot image dataset: Convert the full sunspot image to an image format recognizable by the VGG-16 network; use the image annotation tool to create a sunspot image dataset according to the Zurich classification method;

[0023] Specifically, the full sunspot image in HMI format is converted into JPG / PNG format, and then the sunspot image dataset is created using the labelimg tool according to the Zurich classification method.

[0024] Step 2: Sunspot description text dataset: Manually add its corresponding feature description to each sunspot image in the classified sunspot image dataset obtained in step 1; the feature description is based on each sunspot in each sunspot image. The group is described as an object, and the specific description content at least includes: the class to which the corresponding sunspot group belongs, an...

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Abstract

The invention relates to a method for describing sunspot groups in a full sun image, belonging to the fields of computer vision and natural language processing. In the present invention, by making a data set of sunspot group images and description texts, the original images are first sent into the improved VGG-16 network to generate feature maps, and then the output feature maps are sent to the positioning layer, which is generated by the improved Inception-RPN Candidate regions are finally processed into fixed-size region features, which are processed into one-dimensional vectors that can be processed by LSTM after passing through the recognition network, and finally generate description sentences; compared with traditional methods, the present invention can obtain more accurate Candidate regions, which improve the description quality of the entire network.

Description

technical field [0001] The invention relates to a method for describing sunspot groups in an all-solar image, belonging to the fields of computer vision and natural language processing. Background technique [0002] Sunspot groups on the surface of the sun are abundant in forms, and sunspot groups with different forms are closely related to solar activity. Therefore, accurate detection and description of sunspot groups in all-solar images can provide a basis for monitoring and predicting solar activity. [0003] Image description is to automatically generate a piece of descriptive text according to the given picture, which is a description of the properties of each component in the image and the relationship between them. The existing methods are mainly divided into the following three categories: template-based methods, which are simple and intuitive, but due to the limitation of fixed sentence templates, the generated description sentence structure is often single and rigi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/51G06F16/583G06F16/55G06V10/25G06V10/764G06V10/82G06K9/62G06N3/04
CPCG06F16/51G06F16/583G06F16/55G06V10/25G06N3/045G06F18/241
Inventor 杨云飞刘海燕朱健李小洁
Owner KUNMING UNIV OF SCI & TECH
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