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Articles 1 - 3 of 3
Full-Text Articles in Computer Engineering
Rdlnn-Based Image Forgery Detection And Forged Region Detection Using Mot, Akram Hatem Saber, Mohd Ayyub Khan, Basim Galeb Mejbel
Rdlnn-Based Image Forgery Detection And Forged Region Detection Using Mot, Akram Hatem Saber, Mohd Ayyub Khan, Basim Galeb Mejbel
Karbala International Journal of Modern Science
Image forgery detection TEMPhas become an emerging research area due to the increasing number of forged images circulating on the internet and other social media, which leads to legal and social issues. Image forgery detection includes the classification of an image as forged or authentic and as well as localizing the forgery wifin the image. In this paper, we propose a Regression Deep Learning Neural Network (RDLNN) based image forgery detection followed by Modified Otsu Thresholding (MOT) algorithm to detect the forged region. The proposed model comprises five steps that are preprocessing, image decomposition, feature extraction, classification and block matching. …
Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami
Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami
Future Computing and Informatics Journal
This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …
Deepfakes, Shallowfakes, And The Need For A Private Right Of Action, Eric Kocsis
Deepfakes, Shallowfakes, And The Need For A Private Right Of Action, Eric Kocsis
Dickinson Law Review (2017-Present)
For nearly as long as there have been photographs and videos, people have been editing and manipulating them to make them appear to be something they are not. Usually edited or manipulated photographs are relatively easy to detect, but those days are numbered. Technology has no morality; as it advances, so do the ways it can be misused. The lack of morality is no clearer than with deepfake technology.
People create deepfakes by inputting data sets, most often pictures or videos into a computer. A series of neural networks attempt to mimic the original data set until they are nearly …