INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Waste of Electronic and Electrical Equipment (WEEE) or e-waste is generated at an increasing rate throughout the world. The high demand for electronic devices used in daily activities led to the development of e-wastage. The improper disposal of e-waste has an adverse effect on the environment and human health. For better recycling, e-waste must be properly classified, since each electronic device contains different types of hazardous elements. Manual sorting of e-waste is a very hazardous, expensive, and time-consuming process. The need for automatic e-waste classification is addressed in this paper using YOLOv5. The dataset used for evaluation contains 1350 RGB images that are classified into 10 categories. After training the model for 50 epochs, the mAP, precision, recall and F1score are 99.6, 99.8, 95.5 and 97.6 respectively.
Keywords:
E-waste classification, Deep Learning
Cite Article:
"An Automatic e-waste Classification Model by Improved Deep Learning Algorithm", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.b350-b354, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311145.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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