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Mobile Visual Search applications are emerging that enable users to sense their surroundings with smart phones. This study includes that this type of search engine uses techniques of query by example or Image query by example, which use the content, shape, texture and colour of the image to compare them in a database and then deliver the approximate results from the query. In this paper first we propose MVS (Mobile Visual Search). Second we have our basic component neural networks and discuss about the architecture of the model with CNN image classification. Optical Character Recognition, or OCR is used, this method converts a scanned image into text.
Keywords:
Mobile Visual Search, Neural Networks, CNN, Optical Character Recognition
Cite Article:
"Survey paper on object identification using Mobile Visual Search", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.5, Issue 5, page no.41 - 43, May-2020, Available :http://www.ijrti.org/papers/IJRTI2005007.pdf
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000204804
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