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  Published Paper Details:

  Paper Title

IDENTIFYING MISSING CHILD BY USING MULTICLASS SVM AND CNN

  Authors

  Setti Charan Sai,  Vanyamreddy Chandu,  Pyla Rahul Raj,  Rali Vijay Kiran Acharya

  Keywords

Multiclass SVM, CNN, Machine Learning

  Abstract


It is estimated that a child goes missing in India every eight minutes. This paper presents a novel by using a deep learning methodology for identifying the missing person. The public can upload photographs of a suspicious child in our portal by their landmarks and remarks. The photo will be automatically compared with registered photos of missing child. Classification of input child image and photo with the best match will be selected from the database which contains missing children photos. The Convolutional Neural Network (CNN), a highly effective deep learning technique for image-based applications is adopted here for face recognition. Face descriptors are extracted from the images using a pre-trained CNN model VGG-Face deep architecture. Compared with normal deep learning applications, our algorithm uses convolution network only as a high-level feature extractor, and the child recognition is done by the trained SVM classifier.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT22A6169

  Paper ID - 221387

  Page Number(s) - b280-b285

  Pubished in - Volume 10 | Issue 6 | June 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Setti Charan Sai,  Vanyamreddy Chandu,  Pyla Rahul Raj,  Rali Vijay Kiran Acharya,   "IDENTIFYING MISSING CHILD BY USING MULTICLASS SVM AND CNN", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 6, pp.b280-b285, June 2022, Available at :http://www.ijcrt.org/papers/IJCRT22A6169.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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