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)
The way people dress is fundamentally tied to social identity, and can offer clues about financial status, social status, tastes, and even culture. An algorithm that can identify clothes can help garment companies understand the profile of potential buyers and focus on targeted niche sales, as well as develop campaigns based on customer tastes. Also, this helps the online buyers to identify the damaged cloths and the original quality of the cloth using tags. The tags from the original manufacturers which is embedded with an IC is scanned and the real quality, prices. In this context, convolutional neural network models have been shown to be efficient in the task of image classification. This paper explores and analyzes models of convolutional neural networks in the task of classifying parts of clothing through images. The models tested and compared in this paper obtained greater accuracy when compared to non-convolutional models in the literature.
Keywords:
Fabric defects, neural network, the literature.
Cite Article:
"Automated Fabric Defect Detection Using Deep Learning Techniques", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.c497-c503, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404289.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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