Journal article Open Access

Age and Gender Based Organisation of Shelter Homes using Convolutional Neural Networks

Shravya Suresh; Sneha Venkatesh; Vidya Shree S; Hemalatha V R; T Vijaya Kumar


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="URL">https://zenodo.org/record/5410783</identifier>
  <creators>
    <creator>
      <creatorName>Shravya Suresh</creatorName>
      <affiliation>Student, Department of Computer Science and Engineering, Bangalore Institute of Technology, Bengaluru, India.</affiliation>
    </creator>
    <creator>
      <creatorName>Sneha Venkatesh</creatorName>
      <affiliation>Student, Department of Computer Science and Engineering, Bangalore Institute of Technology, Bengaluru, India.</affiliation>
    </creator>
    <creator>
      <creatorName>Vidya Shree S</creatorName>
      <affiliation>Student, Department of Computer Science and Engineering, Bangalore Institute of Technology, Bengaluru, India.</affiliation>
    </creator>
    <creator>
      <creatorName>Hemalatha V R</creatorName>
      <affiliation>Student, Department of Computer Science and Engineering, Bangalore Institute of Technology, Bengaluru, India.</affiliation>
    </creator>
    <creator>
      <creatorName>T Vijaya Kumar</creatorName>
      <affiliation>Associate Professor,  Department of Computer Science and Engineering, Bangalore Institute of Technology, Bengaluru, India.</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Age and Gender Based Organisation of Shelter Homes using Convolutional Neural Networks</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <subjects>
    <subject>Age Prediction, Gender Prediction Convolutional  Neural Networks, Deep Learning, Shelter Home Organization.</subject>
    <subject subjectScheme="issn">2249-8958</subject>
    <subject subjectScheme="handle">100.1/ijeat.F29920810621</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  and Sciences Publication (BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2021-08-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5410783</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2249-8958</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.F2992.0810621</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The number of abandoned, homeless and poor people have increased drastically in the recent days. Allotting these people to different shelter home is a very difficult task because volunteers in NGO have to do all the work manually and homeless people don&amp;rsquo;t have valid documentation regarding their Age and Gender. Volunteers usually estimate the person&amp;rsquo;s Age and Gender on the basis of naked eye estimation but this estimation or prediction sometimes will not be accurate. This problematic situation can be solved by using Deep Learning algorithm like Convolutional Neural Network (CNN). So in our project, we use CNN algorithm to estimate the Age and Gender from the facial image which proves to be a challenging task for a machine due to the high extent of variability, lighting and other supporting conditions. The system proposes building a model which has multiple convolutional layers along with dropout and maxpooling layers in between. The proposed model has been trained on UTKFace dataset and Fairface dataset. The proposed system aims to produce a high accuracy in allotting the right shelter home for people under various Age and Gender. The web application also accepts donations from the users visiting the website who are willing to help the shelter home residents.&lt;/p&gt;</description>
  </descriptions>
</resource>
14
17
views
downloads
Views 14
Downloads 17
Data volume 9.8 MB
Unique views 14
Unique downloads 17

Share

Cite as