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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

Issue per Year : 12

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Issue Published : 118

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Paper Title: Different Detection Techniques Used to Segregate the Content Generated From AI Or Human
Authors Name: N Venkatesh Kamath , Sandesh Bhat
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IJRTI_186034
Published Paper Id: IJRTI2304080
Published In: Volume 8 Issue 4, April-2023
DOI:
Abstract: This research explores different detection techniques used to segregate content generated by humans and AI. The prevalence of fake news and manipulated images or videos has become a significant issue in the internet and social media age. A dataset of text and image samples generated by AI and human sources was collected and preprocessed. Two feature extraction methods, TF-IDF for text samples and LBP for image samples, were used in this study, and several machine learning algorithms, such as Decision Tree, Random Forest, and Support Vector Machine, were trained on the extracted features. The performance of each algorithm was evaluated using metrics such as accuracy, precision, recall, and F1 score. The study concludes that these techniques can effectively detect fake content generated by humans and AI.
Keywords: Fake Images, AI Detection, Fake Content, Fake News, Segregation
Cite Article: "Different Detection Techniques Used to Segregate the Content Generated From AI Or Human", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.488 - 491, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304080.pdf
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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: IJRTI2304080
Registration ID:186034
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 488 - 491
Country: Mangalore, Karnataka, India
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2304080
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2304080
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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