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A lightweight convolutional neural network for target detection in an edge environment — arXiv:2611.09756

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.09756
License (as archived): CC0-1.0
Archived: 2026-11-09T22:45:28.654Z
SHA-256 of the archived text: 8ef30252dc19c72658ff72f2853c32462d3cee4f63594f043dd39c54e8e36d4c
Stable URL of this page: https://metraipolis.com/documento/dc_ba00a378fa92

How to cite

A lightweight convolutional neural network for target detection in an edge environment — arXiv:2611.09756 — arXiv (en), https://arxiv.org/abs/2611.09756 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ba00a378fa92 (Metraipolis archive dc_ba00a378fa92, sha256 8ef30252dc19c72658ff72f2853c32462d3cee4f63594f043dd39c54e8e36d4c)

BibTeX

@misc{dcba00a378fa92,
  title = {A lightweight convolutional neural network for target detection in an edge environment — arXiv:2611.09756},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.09756},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ba00a378fa92; sha256 8ef30252dc19c72658ff72f2853c32462d3cee4f63594f043dd39c54e8e36d4c},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.09756. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

This paper proposes a novel, lightweight convolutional neural network (CNN) designed for edge device deployment. The CNN is developed to recognize and classify threats or targets of interest. The model is equipped with a real-time hotspot detection algorithm, which enables it to process information quickly and accurately, resulting in improved inference time of up to 20 fps and a detection range of more than 400 meters with typical thermal situational awareness sensors. The proposed CNN has been rigorously tested and validated to demonstrate its high accuracy, sensitivity, and low false positive rate, providing a reliable solution for edge devices to detect potential targets. Additionally, the lightweight design of the CNN allows for easy deployment, making it an ideal solution for extending the security bubble for edge devices. The proposed model can be used for a variety of applications, including surveillance, security, and object recognition.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv cs.CV, nuovi lavori del giorno).
Categorie arXiv: Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2611.09756 — 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 2026-11-09T22:37:47.234Z dalla pagina https://arxiv.org/list/cs.CV/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).