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A repo designed to convert audio-based "weak" labels to "strong" intraclip labels. Provides a pipeline to compare automated moment-to-moment labels to human labels. Methods range from DSP based foreground-background separation, cross-correlation based template matching, as well as bird presence sound event detection deep learning models!
This system utilizes Optical Character Recognition (OCR) extracts text, while computer vision techniques map document layout. Then, SIFT (Scale-Invariant Feature Transform) cleverly matches documents to pre-defined templates, even with variations. This intelligent matching helps identify potential fraud for further investigation.
DiallelX is a CPU-oriented modern fortran program to approximate Network Cross-Correlation coefficients (NCCs) among multiple continuous records and template waveforms observed at multiple seismic stations. The results, relatively less accurate but sufficient to find new seismic events, are obtained several-fold faster than a conventional scheme.