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In recent years, CNNs have begun to see wider adoption in astronomy. In today's high-tech world, these kinds of computer programs are everywhere, used in everything from medical imaging, stock markets and data analytics, to how Netflix generates recommendations based on your viewing history. This is where convolutional neural networks, or CNNs, come in. Sometimes citizen scientists are recruited to help classify galaxy shapes in projects like Galaxy Zoo, but this still takes time." "We're talking several million galaxies over the next few years.
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Mr Cavanagh said that with larger surveys of the sky happening all the time, astronomers are collecting too many galaxies to look at and classify on their own. "Classifying the shapes of galaxies is an important step in understanding their formation and evolution, and can even shed light on the nature of the Universe itself." "Galaxies come in different shapes and sizes" said lead author Mitchell Cavanagh, a PhD candidate based at The University of Western Australia node of the International Centre for Radio Astronomy Research (ICRAR). In new researchm astrophysicists from Australia have used machine learning to speed up a process that is often done manually by astronomers and citizen scientists around the world. Astronomers have designed and trained a computer program which can classify tens of thousands of galaxies in just a few seconds, a task that usually takes months to accomplish.