{"id":691,"date":"2020-10-11T05:59:00","date_gmt":"2020-10-11T05:59:00","guid":{"rendered":"https:\/\/zhengfangs.com\/?p=691"},"modified":"2022-01-13T21:36:54","modified_gmt":"2022-01-13T21:36:54","slug":"machine-learning-approaches-on-china-national-exhibitions-of-fine-arts","status":"publish","type":"post","link":"https:\/\/zhengfangs.com\/?p=691","title":{"rendered":"\u5bf9\u4e8e\u5168\u56fd\u7f8e\u5c55\u7684\u673a\u5668\u5b66\u4e60\u5206\u6790 Machine Learning Approaches on China National Exhibitions of Fine Arts"},"content":{"rendered":"\n
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UMAP_montage<\/figcaption><\/figure><\/div>\n\n\n\n
<\/div>\n\n\n\n

The China National Exhibitions of Fine Arts is one of the most important exhibitions in China. <\/p>\n\n\n\n

If you want to get the title of professor, you have to win this competition.<\/p>\n\n\n\n

I have collected images from the 9th to 13th award-winning works over two decades. The dataset has 2,684 images and 13.7 GB in total.<\/p>\n\n\n\n

Then I used TensorFlow to classify them. We can easily see several broad categories, such as city streets, military life, farmers, ethnic minorities, etc.<\/p>\n\n\n\n

You can find the details through my Google Colab<\/a> project<\/p>\n\n\n\n