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All-sky aurora image classification method and system

A classification method and all-sky technology, applied in the field of computer vision, can solve the problems of huge data volume and missing labels, and achieve the effect of high generation accuracy and high accuracy.

Pending Publication Date: 2021-07-16
NAT SPACE SCI CENT CAS
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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem of huge amount of data and missing labels in the prior art. A semi-supervised learning model based on variational autoencoder is used to ensure that a higher training result

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  • All-sky aurora image classification method and system
  • All-sky aurora image classification method and system

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Embodiment Construction

[0041] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0042] Based on the variational autoencoder and the semi-supervised generation model, the present invention proposes a semi-supervised learning model based on the variational autoencoder. In order to solve the classification problem of unlabeled data, the model of the variational autoencoder is added A classifier is proposed, and a multi-layer convolutional neural network is used for the network among the encoder, decoder and classifier. In this model, the input data is divided into two types, one is labeled data and the other is unlabeled data. Different loss functions are used for the two types of data, and the variational inference process is also different.

[0043] For the generation and inference process of labeled data, you can use figure 1 To represent. The solid line represents the generative process, and the dashed line represent...

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Abstract

The invention discloses an all-sky aurora image classification method and system. The method comprises the steps that: all-sky aurora images to be classified are preprocessed; the preprocessed all-sky aurora image is input into a pre-trained classifier, a classification result is output, and the classification result is in an arc shape, a valance slow coronal shape, a radiation coronal shape or a hot spot shape; and the classifier, the encoder and the decoder form an integral model for joint training. According to the method, the aurora images can be trained and classified under the condition that the data size is huge and only a small number of labels exist, and high accuracy is obtained; and, according to the method, all-sky aurora image classification learning is carried out under the condition that only a small number of labels exist, the semi-supervised generation model based on the variational auto-encoder is used, and all-sky aurora image classification can be carried out with high accuracy.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to an all-sky aurora image classification method and system. Background technique [0002] Solar activities such as flares and coronal mass ejections will generate a large amount of high-energy charged particle flow, which has a major impact on the earth's magnetic field. Not only will communication satellites, space vehicles, and radio signals fail, but in severe cases, the strong current will even seriously interfere with the ground power transmission line. . The north and south poles are the key areas of the solar-terrestrial space. The geomagnetic field enters and exits the polar region almost vertically and extends outward to the magnetosphere and interplanetary space, making the polar region a window for the earth to open to space, and solar wind energy and particles enter the earth The entrance of space is also the most direct area of ​​solar wind-magnetosphere-ionosphere coup...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06T3/60G06T5/00G06T7/11G06T7/13
CPCG06T7/13G06T7/11G06T3/60G06N3/045G06F18/214G06T5/70Y02A90/10
Inventor 蒋家楠李云龙邹自明佟继周
Owner NAT SPACE SCI CENT CAS
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