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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
DEEPFAKE DETECTION ON FACE IMAGES & VIDEOS USING DEEP LEARNING
Authors
B. Manish,C. Manish,B. Sai Kiran Reddy
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Keywords
Deep Learning, Image Classification, Deep Fake Detection, Convolutional Neural, Networks (CNN), Image Processing, Xception, MobileNet, Face Forensics++.
Abstract
ABSTRACT
In recent months, unfastened deep studying-based totally software program tools have facilitated the creation of credible face exchanges in photographs that depart few traces of manipulation, in what they may be referred to as deep faux face detection. Manipulations of digital pics were validated for numerous decades through the coolest use of visual consequences, latest advances in deep studying have caused a drastic increase in the realism of fake content and the accessibility in which it could be created. Those so-called AI-synthesized media (popularly known as fake). Creating fake photographs using Artificially clever gear are easy undertaking. But, with regards to the detection of those fake pictures, it's far a first-rate task. Because education the set of rules to identify the faux pics isn't always simple. We've got taken a step forward in detecting the fake images using a Convolutional Neural network. The system uses a convolutional Neural network (CNN) to extract functions at the body level. These capabilities are used to teach a CNN model which learns to classify if a given photograph has been challenged to manipulation or no longer. Anticipated result against a massive set of faux pix collected from the same old records set. We display how our system can be competitive and bring about this undertaking effect by using an easy architecture. Deep faux and real picture classification. The use of Deep studying is an emerging discipline that specializes in distinguishing between laptop-generated (deep fake) and authentic pictures. The rapid advancement in the era has made it increasingly more difficult to detect these deep fakes, as they come to be greater practical. This undertaking employs deep learning techniques to address this challenge, aiming to increase an effective and efficient model for accurate classification. This topic is selected due to the increasing occurrence and dangers related to deep faux technology. As deep fakes grow to be extra commonplace and convincing, the potential for misuse in various sectors turns into a widespread situation. Growing powerful detection methods is crucial to mitigate these risks and ensure the integrity and trustworthiness of virtual media.
IJCRT's Publication Details
Unique Identification Number - IJCRT24A5778
Paper ID - 262950
Author type - Indian Author
Page Number(s) - p753-p766
Pubished in - Volume 12 | Issue 5 | May 2024
DOI (Digital Object Identifier) -
No Of Downloads - 7
Author Country - India, 500083, Hyderabad, Hyderabad, 500083, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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B. Manish,C. Manish,B. Sai Kiran Reddy, "DEEPFAKE DETECTION ON FACE IMAGES & VIDEOS USING DEEP LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 5, pp.p753-p766, May 2024, Available at :http://www.ijcrt.org/papers/IJCRT24A5778.pdf
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The International Journal of Creative Research Thoughts (IJCRT) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies.
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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