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Combining Deep Learning Mechanisms to Predict Interests from Gaze

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By Fumiko Harada, Hiromitsu Shimakawa, Aoba Izumi
| preprints.org
You are already at the latest version The paper proposes a model to predict users’ personal interests from their gaze. Current image processing technologies enable us to identify each user’s gaze and pupil diameter. However, they cannot identify user interests. The model uses deep learning technologies. It consists of mechanisms to handle the two kinds of gaze: one specific to individuals and the other common to many people.
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