Researchers have taught AI to classify tens of thousands of galaxies

Research team consisting mainly of scientists from the National Astronomical Observatory

Japan (NAOJ), applied the deeptraining, a type of AI, to classify galaxies in a large dataset of images acquired by the Subaru telescope. Thanks to the high sensitivity, 560,000 galaxies were detected in the images. It would be extremely difficult to visually process this large number of galaxies one by one with human eyes for morphological classification. AI allowed the team to complete the processing without human intervention.

National Astronomical Observatory of Japan

Автоматизированные методы обработки для Extraction and evaluation of functions using deep learning algorithms has been developing rapidly since 2012. They are now generally superior to humans in accuracy and are used for autonomous vehicles, security cameras, and many other applications. Dr. Ken-ichi Tadaki, associate professor of the project at NAOJ, suggested the idea that if AI can classify images of cats and dogs, it should be able to distinguish "galaxies with spiral patterns" from "galaxies without spiral patterns." Indeed, using training data prepared by humans, the AI ​​has successfully classified the morphology of galaxies with 97.5% accuracy. Then, by applying the trained AI to the full dataset, he identified spirals in roughly 80,000 galaxies.

Now that this technique has proven its effectivenessefficiency, it can be extended to classify galaxies into more detailed classes by training the AI ​​based on a significant number of them classified by humans. NAOJ currently runs the citizen science project Galaxy Cruise, in which citizens study images taken with the Subaru Telescope, looking for features that indicate a galaxy is colliding or merging with another galaxy.

Galaxy Cruise project consultant Associate Professor Masayuki Tanaka has high hopes for studying galaxies using artificial intelligence.

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