https://journals.itiud.org/index.php/paradigmplus ITI Research Group en-US ParadigmPlus 2711-4627 https://journals.itiud.org/index.php/paradigmplus/article/view/56 <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> Allah Rakhio Copyright (c) 2024 ParadigmPlus https://creativecommons.org/licenses/by/4.0 2024-03-19 2024-03-19 5 1 1 11