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Main Authors: Chandani Lachke, Anushka Singh, Snehal Bhosarkar, Pradnya Jambhale
Format: Recurso digital
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Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.20114909
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author Chandani Lachke
Anushka Singh
Snehal Bhosarkar
Pradnya Jambhale
author_facet Chandani Lachke
Anushka Singh
Snehal Bhosarkar
Pradnya Jambhale
contents <p><strong><span>Deep learning has proven effective in a variety of tough issues, including computer vision, human-level control, and large data analytics. However, as deep learning technology advanced, software was developed that jeopardized national security, democracy, and privacy. Deepfake is a new technology that uses deep learning to create fake photos and videos that look very real. It's important to have tools that can automatically detect and check the quality of these AI-created images and videos. These systems help us quickly tell if a picture or video is real, edited, or fake, and they ensure that the quality is good and not misleading. An investigation of the strategies used to construct the most significant deepfakes, as well as the approaches proposed in the literature for detecting them. We provide a complete examination of the difficulties highlighted by deepfake technology, as well as recommendations for future and upcoming research opportunities. It also supports creating new and more reliable ways to handle deepfakes as they become more complex.</span></strong></p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_20114909
institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Development of AI/ML Based Solutions for Deep Fake Detection
Chandani Lachke
Anushka Singh
Snehal Bhosarkar
Pradnya Jambhale
<p><strong><span>Deep learning has proven effective in a variety of tough issues, including computer vision, human-level control, and large data analytics. However, as deep learning technology advanced, software was developed that jeopardized national security, democracy, and privacy. Deepfake is a new technology that uses deep learning to create fake photos and videos that look very real. It's important to have tools that can automatically detect and check the quality of these AI-created images and videos. These systems help us quickly tell if a picture or video is real, edited, or fake, and they ensure that the quality is good and not misleading. An investigation of the strategies used to construct the most significant deepfakes, as well as the approaches proposed in the literature for detecting them. We provide a complete examination of the difficulties highlighted by deepfake technology, as well as recommendations for future and upcoming research opportunities. It also supports creating new and more reliable ways to handle deepfakes as they become more complex.</span></strong></p>
title Development of AI/ML Based Solutions for Deep Fake Detection
url https://doi.org/10.5281/zenodo.20114909