Bibliometric Analysis of Passive Image Forgery Detection and Explainable AI

Authors

Kalyani Dhananjay Kadam, Symbiosis Institute of Technology ,Symbiosis International UniversityFollow
Dr. Swati Ahirrao Ahirrao, Symbiosis Institute of Technology , Symbiosis International UniversityFollow
Dr. Ketan Kotecha, Head, SCAAI ,Symbiosis International UniversityFollow

Document Type

Article

Citation

Kadam, K.D., Ahirrao, S. N.,Dr. Ketan Kotecha (2020). Bibliometric Analysis of Passive Image Forgery Detection and Explainable AI. Library Philosophy and Practice, 1-29.

Abstract

Due to the arrival of social networking services such as Facebook and Instagram, there has been a vast increase in the volume of image data generated in the last decade. The use of image processing tools like GNU Gimp, Adobe Photoshop to create doctored images and videos is a major concern. These are the main sources of fake news and are often used in malevolent ways such as for mob incitement. Before a move can be taken based on a fake image, we should confirm its realness. This paper shows systematic mappings of existing literature for image forgery detection using deep learning and explainable AI. This uses the Scopus database for data analysis and various tools such as Sciencescape, Gephi, Tableau and VOS Viewer. The study discovered that the largest number of reviews on image forgery detection using deep learning and explainable AI had explored very recently. It was observed that USA universities/institutions are foremost in the research studies focusing on this research topic.