Difference between revisions of "Auto clustering of galaxies after dimensionality reduction"
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(1) In the first step, we first filter out the galaxy data with data shape [3*256*256], and save the galaxy data paths that match this shape into a text file, which constitutes our training set. | (1) In the first step, we first filter out the galaxy data with data shape [3*256*256], and save the galaxy data paths that match this shape into a text file, which constitutes our training set. | ||
From more than 300，000 data, 290613 galaxies data matching the shape conditions were selected. | From more than 300，000 data, 290613 galaxies data matching the shape conditions were selected. | ||
[[File:微信图片_20220304222539.png|500px|center]] | |||
Revision as of 14:15, 4 March 2022
This work is divided into two parts. The first part is to reduce the dimension of Galaxy data to low dimensional space with VAE. (1) In the first step, we first filter out the galaxy data with data shape [3*256*256], and save the galaxy data paths that match this shape into a text file, which constitutes our training set. From more than 300，000 data, 290613 galaxies data matching the shape conditions were selected.
