FRTSearch reframes fast radio transient detection as instance segmentation on dynamic spectra and uses the segmented shapes to infer dispersion measure and time of arrival, achieving 98% recall with over 99.9% fewer false positives than traditional methods.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Deep learning identifies voids in NGC 628 with low association to known star clusters, supporting an evolutionary sequence from molecular clouds via stellar feedback to detached voids.
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FRTSearch: Unified Detection and Parameter Inference of Fast Radio Transients using Instance Segmentation
FRTSearch reframes fast radio transient detection as instance segmentation on dynamic spectra and uses the segmented shapes to infer dispersion measure and time of arrival, achieving 98% recall with over 99.9% fewer false positives than traditional methods.
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Automated void identification by Blendmask: from hierarchical molecular gas to hierarchical voids in NGC 628
Deep learning identifies voids in NGC 628 with low association to known star clusters, supporting an evolutionary sequence from molecular clouds via stellar feedback to detached voids.