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    Deep Learning Technique Could Speed the Search for Galaxy Clusters

    Article obtained from Photonics RSS Feed.

    Deep-CEE, a deep learning technique developed by scientists at Lancaster University, can efficiently localize and classify objects in wide-field color images to identify galaxy clusters in deep space.

    Deep-CEE — which refers to Deep Learning for Galaxy Cluster Extraction and Evaluation — builds on the work of astronomer George Abell, who in the 1950s manually analyzed around 2000 photographic plates to look for visual signatures of galaxy clusters. Deep-CEE’s developers used Abell galaxy clusters as the ground-truth labels in color images to develop an artificial intelligence (AI) model based on neural networks. The researchers trained the AI model to identify galaxy clusters by showing it examples of known, labeled…

    Jul, 09 2019 |

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