Scientists from Australia and Denmark trained a deep learning system to classify and predict the ages of red giant stars.
“Automated methods do exist, however considerable effort is required for defining and acquiring features,” mentioned the researchers in their paper in reference to why they leveraged deep learning for their work over conventional methods. “Furthermore, these methods require relatively high signal-to-noise data.”
Using NVIDIA GPUs, Keras and cuDNN with the Theano deep learning framework, they trained their convolutional neural network on 5,000 Kepler red giants. Once trained, they were able to predict the ages of red giants with 99% accuracy, classify 5,379 which have never been analyzed in the past and corrected 500 that other researchers had incorrectly classified.
This research give scientists hope that more red giants will be located in the galaxy and the deep learning method will allow them to date red stars faster and with higher accuracy.
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May 30, 2017
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AI-Generated Summary
- Scientists from Australia and Denmark used a deep learning system to classify and predict the ages of red giant stars, as traditional methods require significant effort and high-quality data.
- The researchers trained a convolutional neural network on 5,000 Kepler red giants using NVIDIA GPUs and achieved 99% accuracy in predicting the ages of red giants.
- This research enables scientists to date red stars faster and with higher accuracy, and has already led to the classification of 5,379 previously unanalyzed red giants and the correction of 500 previously misclassified ones.
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