Enhancing Image Forgery Detection: A Novel Method for Content-Preserving Forgeries using Machine Learning Algorithms
Improving Accuracy and Reliability of Image Forgery Detection using Machine Learning
Keywords:
image forgery detection, content-preserving forgeries, machine learning algorithms, support vector machines, convolutional neural networks, ensemble classifiers, accuracy, reliabilityAbstract
Digital image forgery has become a significant concern due to the ease of manipulating anddistributing digital media. Content-preserving forgeries are particularly challenging to detect, as theymaintain the visual integrity of the original image while altering its content. In this research paper, wepropose a novel image forgery detection method that combines Support Vector Machines (SVM),Convolutional Neural Networks (CNN), and ensemble classifiers to enhance the accuracy and reliabilityof forgery detection.Published
2021-12-01
How to Cite
[1]
“Enhancing Image Forgery Detection: A Novel Method for Content-Preserving Forgeries using Machine Learning Algorithms: Improving Accuracy and Reliability of Image Forgery Detection using Machine Learning”, JASRAE, vol. 18, no. 7, pp. 462–463, Dec. 2021, Accessed: Sep. 19, 2024. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/13671
Issue
Section
Articles
How to Cite
[1]
“Enhancing Image Forgery Detection: A Novel Method for Content-Preserving Forgeries using Machine Learning Algorithms: Improving Accuracy and Reliability of Image Forgery Detection using Machine Learning”, JASRAE, vol. 18, no. 7, pp. 462–463, Dec. 2021, Accessed: Sep. 19, 2024. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/13671