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Signal-Centric Remote Sensing via Alternative Preprocessing and Acoustic Processing for ML-Driven Applications — arXiv:2609.21123

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.21123
License (as archived): CC0-1.0
Archived: 2026-10-10T01:44:44.101Z
SHA-256 of the archived text: 787427913ac7df1180ab70ac44102445efea9fc389f59ecc60b17e9622b332e3
Stable URL of this page: https://metraipolis.com/documento/dc_ceaccfe34366

How to cite

Signal-Centric Remote Sensing via Alternative Preprocessing and Acoustic Processing for ML-Driven Applications — arXiv:2609.21123 — arXiv (en), https://arxiv.org/abs/2609.21123 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ceaccfe34366 (Metraipolis archive dc_ceaccfe34366, sha256 787427913ac7df1180ab70ac44102445efea9fc389f59ecc60b17e9622b332e3)

BibTeX

@misc{dcceaccfe34366,
  title = {Signal-Centric Remote Sensing via Alternative Preprocessing and Acoustic Processing for ML-Driven Applications — arXiv:2609.21123},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.21123},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ceaccfe34366; sha256 787427913ac7df1180ab70ac44102445efea9fc389f59ecc60b17e9622b332e3},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.21123. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

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.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-21 in cs.LG).
Categorie arXiv: Machine Learning (cs.LG) ; Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2609.21123 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-10T01:14:16.611Z dalla pagina https://arxiv.org/catchup/cs.LG/2026-09-21?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).