SOURCE-LINKED INTELLIGENCE
Signal-Centric Remote Sensing via Alternative Preprocessing and Acoustic Processing for ML-Driven Applications
The dominant method of processing sonar data is using image-based representations, requiring the preprocessing of image data on autonomous systems. We propose an alternative data processing method for remote sensing applications via the use of data in Comma-Seperated Value format. Experimentation on our alternative approach shows a reduction of processing time by 91.18%, an improvement in accurate object detection by Machine Learning, and an increase in SNR (Signal-to-noise ratio), PSNR (Peak signal-to-noise ratio), and other evaluation metrics.
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T22:16:47.000Z
First collected: 2026-09-23T14:01:59.594Z. This is not the publication date.