 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
|
Issue: April 2026
Volume 11 | Issue 4
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 119
Article Submitted : 23355
Article Published : 9033
Total Authors : 23952
Total Reviewer : 831
Total Countries : 162
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | ORPHAN BABY ADOPTION SYSTEM BASED ON PARENT CHILD FACIAL FEATURES |
| Authors Name: | Badisa Pranava Sai , Mohdmaaz.shaikh |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_211103
|
| Published Paper Id: | IJRTI2604062 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | The number of digital forensic investigations involving indecent pictures of children (IIoC) has increased significantly, and one of the main obstacles investigators confront is the laborious process of manually searching images for illegal content. CAID (Child Abuse picture Database) is a standard national repository of IIoC that law enforcement in the UK maintains and utilizes to match picture hashes and information to identify known illicit photos. Faster and more efficient IIoC studies are made possible in large part by the CAID. However, human analysis is necessary for any photos that cannot be matched using CAID. Investigators must view each photograph and confirm that it is IIoC. The estimation of the victim's age in the photos—that is, whether they are an adult or juvenile, as this would alter the investigation's trajectory—is an essential step in this verification process, but it takes time because there are many photos to review, which slows down the investigation. Human investigators find this to be a difficult and time-consuming. Deep learning has the potential to accurately assess age in photos, as previous research has shown. This speeds up the inquiry by lowering the quantity of photos that must be manually processed. However, a comparative study utilizing the same datasets to determine the best deep learning model and classification technique to employ is lacking in terms of practical implementation in IIoC investigations. We have shown that binary classification is the most effective method for identifying photographs as either children or adults, achieving the highest accuracy depends on parent-child facial matching. |
| Keywords: | facial recognition- deep learning- orphan adoption- image processing- child facial matching- adoption system |
| Cite Article: | "ORPHAN BABY ADOPTION SYSTEM BASED ON PARENT CHILD FACIAL FEATURES", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.a455-a462, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604062.pdf |
| Downloads: | 00082 |
| 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 |
| Publication Details: |
Published Paper ID: IJRTI2604062
Registration ID:211103
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: a455-a462 Country: Madhira/ district, Telangana, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604062 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604062 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||