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gazeNet: End-to-end eye-movement event detection with deep neural networks

Zemblys, Raimondas ; Niehorster, Diederick C. ; Holmqvist, Kenneth



Abstract

Existing event detection algorithms for eye-movement data almost exclusively rely on thresholding one or more hand-crafted signal features, each computed from the stream of raw gaze data. Moreover, this thresholding is largely left for the end user. Here we present and develop gazeNet, a new framework for creating event detectors that do not require hand-crafted signal features or signal ...

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