| Autor: |
Cai, Wenming, Xie, Mengyun, Liu, Yayun, Yang, Xuesong |
| Zdroj: |
Journal of Organizational and End User Computing; September 2024, Vol. 36 Issue: 1 p1-16, 16p |
| Abstrakt: |
In response to the growing demands of urbanization, our research presents a pioneering Smart City Waste Classification Management System utilizing advanced computer vision techniques for efficient and accurate waste sorting. This system integrates the innovative CT-Net algorithm, which synergizes the strengths of Convolutional Neural Networks (CNNs) and Transformer architectures to tackle the complex challenges posed by varied and unpredictable urban waste characteristics. Extensive evaluations on multiple datasets, including the proprietary Huawei Cloud waste dataset, demonstrate that our model significantly outperforms existing methodologies in terms of precision, robustness, and processing speed. By deploying this technology within urban waste management frameworks, cities can achieve remarkable improvements in sustainability and operational efficiency. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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