UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 9 Issue 5
May-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2205889


Registration ID:
402911

Page Number

h691-h694

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Title

OBJECT DETECTION WITH COMPUTER VISION USING VGG-19 ARCHITECTURE

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Abstract

The motivation behind this study is to perform the process of object detection with the help of computer vision technology in which we have insert the images in any format which are in .pdf form, .jpg form, .png form, .jpeg form . .gif format. Here we can use the VGG 19 algorithm or we can also use the YOLO algorithm. But VGG 19 is awesome algorithm as it is a convolutional neural network which has 19 deep layers. This study also gives the percentage of accuracy of predictions of object present in the image. The accuracy of this model is 95%.This model is based on transfer learning model in which we use the VGG-19 architecture model based on Convolutional Neural Network (CNN). VGG-19 is a convolutional neural network layer architecture which is mostly utilized for transfer learning process. It consists of 16 convolutional layer,19 learnable weights, 3FC layer and one output layer.

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"OBJECT DETECTION WITH COMPUTER VISION USING VGG-19 ARCHITECTURE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.h691-h694, May-2022, Available :http://www.jetir.org/papers/JETIR2205889.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"OBJECT DETECTION WITH COMPUTER VISION USING VGG-19 ARCHITECTURE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. pph691-h694, May-2022, Available at : http://www.jetir.org/papers/JETIR2205889.pdf

Publication Details

Published Paper ID: JETIR2205889
Registration ID: 402911
Published In: Volume 9 | Issue 5 | Year May-2022
DOI (Digital Object Identifier):
Page No: h691-h694
Country: LUCKNOW/LUCKNOW, UP, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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