492579299Chen/Dataset-Night: YOLO-VSS Low-Light Object Detection Dataset v1.0.0

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Autor principal: 492579299Chen
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Publicado: Zenodo 2026
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author 492579299Chen
author_facet 492579299Chen
contents <p>We release the primary dataset for the YOLO-VSS architecture. We construct these image samples to evaluate object perception under extreme optical degradation. We apply a Poisson-Gaussian heteroscedastic noise model to replicate the photon-starved physical response of edge CMOS sensors. We provide bounding box annotations for concealed targets, specifically handguns and knives, in standard YOLO format. We design this repository to help researchers reproduce the hardware-constrained object detection experiments detailed in our IEEE Internet of Things Journal submission. We trigger this initial release to generate a persistent DOI through the Zenodo integration platform.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19630398
institution Zenodo
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publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle 492579299Chen/Dataset-Night: YOLO-VSS Low-Light Object Detection Dataset v1.0.0
492579299Chen
<p>We release the primary dataset for the YOLO-VSS architecture. We construct these image samples to evaluate object perception under extreme optical degradation. We apply a Poisson-Gaussian heteroscedastic noise model to replicate the photon-starved physical response of edge CMOS sensors. We provide bounding box annotations for concealed targets, specifically handguns and knives, in standard YOLO format. We design this repository to help researchers reproduce the hardware-constrained object detection experiments detailed in our IEEE Internet of Things Journal submission. We trigger this initial release to generate a persistent DOI through the Zenodo integration platform.</p>
title 492579299Chen/Dataset-Night: YOLO-VSS Low-Light Object Detection Dataset v1.0.0
url https://doi.org/10.5281/zenodo.19630398