Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
The world generates at least 3.5 million tons of waste per day and this is still increasing day by day one of the main cause is because of continuous urbanization so to create awareness in the society that , this application is being developed to classify various types of waste materials and suggest reusing and recycling ideas and step wise process to implement a useful item from that specific waste from the image , with the help of this web application a person can simply implement a useful item from the procedure provided in the web interface.
A deep Neural Network is trained on 12000+ images and classified data of around classes of images using Residual Networks architecture with a depth of 152 layers deep which is 8x deeper than VGG networks , This was achieved through a python library OpenCv to identify objects The algorithm classifies image and provides data for respective type of object .
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Cite Article:
"WASTE REUSING AND RECYCLING IMPLEMENTATION USING OPENCV AND DNN", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 3, page no.583 - 585, March-2023, Available :http://www.ijrti.org/papers/IJRTI2303102.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator