Researchers from ATR Computational Neuroscience Laboratories and Kyoto University in Japan developed a deep learning-based algorithm that can generate images from brain activity. ��The reconstruction algorithm starts from a random image and iteratively optimize the pixel values so that the DNN (deep neural network) features of the input image become similar to those decoded from brain activity��
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