Fingerprint clear up analysis. An example of the use of Generative Adversarial Networks. But note the comment on auditing the results in court.
AI Clears Up Images of Fingerprints to Help with Identification
New Scientist, Matthew Sparkes, June 28, 2021
West Virginia University researchers have trained an artificial intelligence (AI) model to clean up distorted images of fingerprints from crime scenes to improve identification. The researchers developed a generative adversarial network by creating blurred versions of 15,860 clean fingerprint images from 250 subjects. They trained the AI using nearly 14,000 of these pairs of images; when they tested its performance on the remainder, they found the model to be 96% accurate at the lower end of the range of blurring intensity, and 86% at the higher end. Forensic Equity's David Goodwin said the use of neural networks to manipulate images would have trouble standing up in court because they cannot be audited like human-generated code, and the inner workings of these models are unknown. ... '
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