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September 5, 2025SensorsOpen Access

A Feasibility Study of Automated Detection and Classification of Signals in Distributed Acoustic Sensing

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Authors

HPH. PedersenTechnical University of DenmarkPHPeder HeiselbergTechnical University of DenmarkHHH. HeiselbergTechnical University of Denmark

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Implication

Feasibility study reveals near-real-time detection of acoustic signals in maritime environments, suggesting improved monitoring capabilities.

Key Points

  • Results show potential for distinguishing between diverse signal sources, including ships and earthquakes.
  • Metrics indicate a Davies–Bouldin Index of 0.828, suggesting effective classification with full dataset.
  • Using principal component analysis, the study examines the separability of labeled data.
  • Clustering quality diminishes notably with exclusion of more than 20% of labeled samples, emphasizing quality in classification.

Cite This Study

Pedersen et al. (2025) studied this question.

synapsesocial.com/papers/68bb5f3e6d6d5674bcd033d0https://doi.org/10.3390/s25175445
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