MIT researchers have developed a neural network of the human brain’s face recognition mechanism, which they claim captures more aspects of human neurology than previous models. The machine learning system designed to implement the researchers' model trained itself to include an intermediate step that calculated the degree of rotation in a face. In their paper, published today in Nature Neuroscience, the team describes how it was able to train its algorithm by analyzing images from thousands of people and then training it on those images.
MIT researchers have developed a neural network of the human brain’s face recognition mechanism, which they claim captures more aspects of human neurology than previous models. The machine learning system designed to implement the researchers' model trained itself to include an intermediate step that calculated the degree of rotation in a face. While it emerged spontaneously, it duplicated an experimentally observed feature of the primate face-processing mechanism, which the researchers claim suggests they are on the right track to creating a "biologically plausible" model of the nervous system.