Researchers have finally created a tool to spot duplicated images across thousands of papers

Description

In a paper published on 22 February on the bioRxiv preprint server1 , a team led by Daniel Acuna, a machine-learning researcher at Syracuse University in New York, report using an algorithm to crunch through hundreds of thousands of biomedical papers, searching for duplicate images. If journal editors adopted similar methods, they might be able to more easily screen images before publication — something that currently requires considerable effort and is done by only a few publications.