Paper Title
A Review on Fake Image Detection Using Machine Learning
Article Identifiers
Authors
Sahil Meshram , Vaishali Gedam , Shrinivas chinchanikar , Yash Lad , Ganesh pandey, Punam Bhandarkar
Keywords
Biometry, Identity, Recognition, Detection, Fake face.
Abstract
Nowadays biometric systems are useful in recognizing a person’s identity, but criminals change their appearance in behaviour and psychological to deceive recognition system. To overcome this problem we are using a new technique called Deep Texture Features extraction from images and then building train machine learning model using CNN (Convolution Neural Networks) algorithm. This technique refers as LBPNet or NLBPNet as this technique is heavily dependent on features extraction using LBP (Local Binary Pattern) algorithm. In this project, we are designing LBP Based machine learning Convolution Neural Network called LBPNET to detect fake face images. Here first we will extract LBP from images and then train LBP descriptor images with Convolution Neural Network to generate a training model. Whenever we upload a new test image then that test image will be applied to the training model to detect whether the test image contains a fake image or a non-fake image. Below we can see some details on LBP.
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How To Cite
"A Review on Fake Image Detection Using Machine Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 4, page no.e78-e83, April-2023, Available :https://ijnrd.org/papers/IJNRD2304413.pdf
Issue
Volume 8 Issue 4, April-2023
Pages : e78-e83
Other Publication Details
Paper Reg. ID: IJNRD_191816
Published Paper Id: IJNRD2304413
Downloads: 000121167
Research Area: Computer Science & TechnologyÂ
Country: Nagpur, maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2304413.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304413
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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