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Autism is a developmental disorder that affects social interaction andcommunication of children. The gold standard diagnostic tools are verydifficult to use and time consuming. However, diagnostic could be deduced fromchild gaze preferences by looking a video with social and abstract scenes. Inthis work, we propose an algorithm based on convolutional neural networks topredict gaze direction for a fast and effective autism diagnosis. Early resultsshow that our algorithm achieves real-time response and robust high accuracyfor prediction of gaze direction.

Prediction of gaze direction using Convolutional Neural Networks for Autism diagnosis