<ul><li>A novel algorithm is presented for detecting fast moving celestial objects within star fields.</li><li>The algorithm enhances neural networks by transforming them into physical-inspired neural networks.</li><li>It leverages the point spread function and observational mode as priors for accurate detection.</li><li>The algorithm is effective in detecting fast moving celestial objects across different observational modes.</li></ul>

Adaptive Detection of Fast Moving Celestial Objects Using a Mixture of Experts and Physical-Inspired Neural Network

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