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Detection method and system of galaxy image

A galaxy and image technology, applied in the field of image processing, can solve problems such as low efficiency, inconsistent standards, and deviations, and achieve the effects of improving resolution, reducing interference, and speeding up the speed

Pending Publication Date: 2022-01-21
SHANDONG UNIV
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Problems solved by technology

[0004] When the galaxy candidates obtained by using the target detection algorithm contain tens of thousands or even hundreds of thousands, the manual inspection process is not only inefficient, but also due to different experience of multiple people checking, it is easy to lead to inconsistent standards and deviations, thus making the result data consistent sexually affected

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  • Detection method and system of galaxy image
  • Detection method and system of galaxy image
  • Detection method and system of galaxy image

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Embodiment Construction

[0040] Embodiments of the present application are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present application, and are not construed as limiting the present application.

[0041] Those skilled in the art will understand that unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the word "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements, components, and / or groups thereof. It will be under...

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Abstract

The invention provides a detection method and system of a galaxy image, which are used for efficiently and automatically detecting an galaxy image in the whole process. The method comprises the following steps: detecting celestial body image samples by using a target detection model, and identifying a galaxy candidate body; acquiring galaxy candidate body image samples by using the galaxy candidate body, wherein the size of each image in the galaxy candidate body image samples is less than that of each image in the celestial body image samples; training an unsupervised neural network by using the galaxy candidate body image samples, and clustering the galaxy candidate body images by using the trained unsupervised neural network to obtain an image data set with category labels; and training a semi-supervised neural network model by using the image data set with the category labels and unlabeled images in the galaxy candidate body image samples, and classifying the galaxy candidate body image samples by using the trained semi-supervised neural network model to obtain galaxy images.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular to a method and system for detecting galaxy images. Background technique [0002] Galaxies refer to the operating system composed of a huge number of star systems and interstellar dust. They are the basic unit of the universe and an important research object in the study of the universe. [0003] At present, galaxy images are obtained through astronomical images, but there are thousands of celestial objects in one image, including stars, galaxies, quasars and other celestial bodies, and the galaxy images obtained by artificial intelligence methods will be mixed. The haloed stars, artifacts and other misidentified images (these images are called galaxy candidate images), however, the analysis of the galaxy candidates in these galaxy candidate images is generally through manual inspection and screening, so as to determine the true galaxy image. [0004] When the g...

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Application Information

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IPC IPC(8): G06V20/00G06V10/762G06V10/774G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/04G06N3/088G06F18/23G06F18/24G06F18/214
Inventor 衣振萍梁增绪刘猛
Owner SHANDONG UNIV
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