INSIGHT: Combining Fixation Visualisations and Residual Neural Networks for Dyslexia Classification From Eye-Tracking Data.

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作者： Roman,Svaricek ^[1] ; Nicol,Dostalova ^[1] ; Jan,Sedmidubsky ^[2] ; Andrej,Cernek ^[2]

作者单位： Department of Educational Sciences, Faculty of Arts, Masaryk University, Brno, Czech Republic. ^[1] Department of Machine Learning and Data Processing, Faculty of Informatics, Masaryk University, Brno, Czech Republic. ^[2]

关键词 AI‐based diagnosis ResNet18 deep learning dyslexia eye movement eye tracking fixation data classification

主题词人类(Humans);阅读障碍(Dyslexia);儿童(Child);女(雌)性(Female);男(雄)性(Male);注视, 眼(Fixation, Ocular);阅读(Reading);眼球运动(Eye Movements)

DOI 10.1002/dys.1801

PMID 39843401

发布时间 2025-01-22

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Dyslexia (Chichester, England)

2025年31卷1期

e1801页

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INSIGHT: Combining Fixation Visualisations and Residual Neural Networks for Dyslexia Classification From Eye-Tracking Data.

Dyslexia (Chichester, England)

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Dyslexia (Chichester, England)

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INSIGHT: Combining Fixation Visualisations and Residual Neural Networks for Dyslexia Classification From Eye-Tracking Data.

Dyslexia (Chichester, England)

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Dyslexia (Chichester, England)

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