Multi-modal learning from video, eye tracking, and pupillometry for operator skill characterization in clinical fetal ultrasound
This paper presents a novel multi-modal learning approach for automated skill characterization of obstetric ultrasound operators using heterogeneous spatio-temporal sensory cues, namely, scan video, eye-tracking data, and pupillometric data, acquired in the clinical environment. We address pertinent...
| Auteurs principaux: | , , , |
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| Format: | Conference item |
| Langue: | English |
| Publié: |
IEEE
2021
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