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An Image Quality Evaluation and Masking Algorithm Based On Pre-trained Deep Neural Networks
With the growing amount of astronomical data, there is an increasing need for automated data processing pipelines, which can extract scientific information from observation data without human interventions.
Image Restoration with Point Spread Function Regularization and Active Learning
Large-scale astronomical surveys can capture numerous images of celestial objects, including galaxies and nebulae.
Detection of Strongly Lensed Arcs in Galaxy Clusters with Transformers
We embed prior information of strongly lensed arcs at cluster-scale into the training data through simulation and then train the detection algorithm with simulated images.
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