March 20, 2024, 4:45 a.m. | Muhammad Umair, Athman Bouguettaya, Abdallah Lakhdari

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.12045v1 Announce Type: new
Abstract: We propose a novel framework for crowdsourced images to determine the likelihood of an image being fake. We use a service-oriented approach to model and represent crowdsourced images uploaded on social media, as image services. Trust may, in some circumstances, be determined by using only the non-functional attributes of an image service, i.e., image metadata. We define intention of changes as a key parameter to ascertain fake image services. A novel framework is proposed to …

abstract arxiv cs.cv fake framework image images likelihood media novel service services social social media trust type

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Field Sample Specialist (Air Sampling) - Eurofins Environment Testing – Pueblo, CO

@ Eurofins | Pueblo, CO, United States

Camera Perception Engineer

@ Meta | Sunnyvale, CA