SOUL-DRIFTER
Life Long Researcher
Now this could be very handy for those unable to talk.
Overview of deep image reconstruction is shown. The pixels’ values of the input image are optimized so that the DNN features of the image are similar to those decoded from fMRI activity. A deep generator network (DGN) is optionally combined with the DNN to produce natural-looking images, in which optimization is performed at the input space of the DGN. Credit: bioRxiv (2017). DOI: 10.1101/240317
More: https://techxplore.com/news/2018-01-japan-decode-thoughts.html
Overview of deep image reconstruction is shown. The pixels’ values of the input image are optimized so that the DNN features of the image are similar to those decoded from fMRI activity. A deep generator network (DGN) is optionally combined with the DNN to produce natural-looking images, in which optimization is performed at the input space of the DGN. Credit: bioRxiv (2017). DOI: 10.1101/240317
Making news this month is a study by researchers the Advanced Telecommunications Research Institute International (ATR) and Kyoto University in Japan, having built a neural network that not only reads but re-creates what is in your mind.
Specifically, "The team has created a first-of-its-kind algorithm that can interpret and accurately reproduce images seen or imagined by a person," wrote Alexandru Micu in ZME Science.
Their paper, "Deep image reconstruction from human brain activity," is on bioRxiv. The authors are Guohua Shen, Tomoyasu Horikawa, Kei Majima, and Yukiyasu Kamitani.
Vanessa Ramirez, associate editor of Singularity Hub, was one of several writers on tech watching sites who reported on the study. The writers noted that this would mark a difference from other research involved in deconstructing images based on pixels and basic shapes.
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More: https://techxplore.com/news/2018-01-japan-decode-thoughts.html