A saliency-guided wavelet framework extracts transient glitches from gravitational-wave strain data by pre-tagging candidates with UMAP, identifying time-frequency regions on CWT spectrograms, and enabling exact reconstruction via adaptive DWT coefficient masking.
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2026 1verdicts
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Wavelet-Based Extraction of Transient Noise in Gravitational-Wave Interferometers using a Saliency-Guided Learning Architecture
A saliency-guided wavelet framework extracts transient glitches from gravitational-wave strain data by pre-tagging candidates with UMAP, identifying time-frequency regions on CWT spectrograms, and enabling exact reconstruction via adaptive DWT coefficient masking.