https://journals.itiud.org/index.php/paradigmplus/issue/feed 2024-04-15T02:04:21+00:00 Hector Florez haflorezf@udistrital.edu.co Open Journal Systems https://journals.itiud.org/index.php/paradigmplus/article/view/56 2024-04-15T02:04:21+00:00 Allah Rakhio allahrakhio54@gmail.com

<p>With the rise of deep learning technologies, the landscape of recycling plant automation has dramatically transformed. This paper presents a pioneering application of YOLOv4 in conjunction with Darknet, tailored specifically to detect hazardous items including spray cans, batteries, and other potential threats. By introducing this state-of-the-art detection mechanism, recycling plants can elevate safety standards, optimize operational processes, ensure adherence to stringent regulatory guidelines, and play a pivotal role in environmental preservation.</p>

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