Researchers at Case Western University have been using 3D imaging to detect forgeries using Artificial Intelligence. Theri success rate is has been as hight as 96%, enough for art conservators to take notice. Here’s more from ArtNet News:
The study asked students from the Cleveland Institute of Arts to paint four identical yellow flowers in bloom. It then fed the results from the profilometer into what are known as convolutional neural networks, which help determine unique characteristics in brushstrokes, akin to fingerprints.
The results identified the ways that brain patterns and nervous system movement are mapped onto the three-dimensional surface of the canvas. “We were blown away when we saw the results,” Singer said. “Remarkably, short-length scales, even as small as a bristle diameter, were the key to reliably distinguishing among artists. These results show promise for real-world attribution, particularly in the case of workshop practice.” This means that art historians may now be able to tell which specific areas of a single canvas were made by artists, their assistants, or forgers.
Every Tuesday is Art Tuesday here at Adafruit! Today we celebrate artists and makers from around the world who are designing innovative and creative works using technology, science, electronics and more. You can start your own career as an artist today with Adafruit’s conductive paints, art-related electronics kits, LEDs, wearables, 3D printers and more! Make your most imaginative designs come to life with our helpful tutorials from the Adafruit Learning System. And don’t forget to check in every Art Tuesday for more artistic inspiration here on the Adafruit Blog!
No comments:
Post a Comment