Mesfer Al Duhayyim1,*, Saud S. Alotaibi2, Shaha Al-Otaibi3, Fahd N. Al-Wesabi4, Mahmoud Othman5, Ishfaq Yaseen6, Mohammed Rizwanullah6, Abdelwahed Motwakel6
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3315-3332, 2023, DOI:10.32604/cmc.2023.033250
Abstract Proper waste management models using recent technologies like computer vision, machine learning (ML), and deep learning (DL) are needed to effectively handle the massive quantity of increasing waste. Therefore, waste classification becomes a crucial topic which helps to categorize waste into hazardous or non-hazardous ones and thereby assist in the decision making of the waste management process. This study concentrates on the design of hazardous waste detection and classification using ensemble learning (HWDC-EL) technique to reduce toxicity and improve human health. The goal of the HWDC-EL technique is to detect the multiple classes of wastes, particularly hazardous and non-hazardous wastes.… More >
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