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arXiv Machine Learning By Logan Luna, Sirio Jansen-S\'anchez, Ilteris Demirkiran, Leo Ghelarducci

Signal-Centric Remote Sensing via Alternative Preprocessing and Acoustic Processing for ML-Driven Applications

Read the original on arXiv Machine Learning →

The paper proposes a new approach to processing sonar data for remote sensing by using CSV-format data instead of traditional image-based representations. Experiments demonstrate a 91.18% reduction in processing time, improved accuracy of machine‑learning object detection, and higher signal‑to‑noise and peak‑signal‑to‑noise ratios.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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