Biography and Research Information
OverviewAI-generated summary
Lydia Rockers' research investigates the application of deep learning techniques for detecting autism spectrum disorder (ASD) using video data. Her work also explores the influence of response conditions on emotions evoked by food imagery, as measured by the Valence × Arousal Circumplex-Inspired Emotion Questionnaire (CEQ).
Rockers has published two papers, achieving an h-index of 2 with 14 total citations. Her scholarly network includes collaborators such as Han‐Seok Seo and Xuan-Bac Nguyen from the University of Arkansas at Fayetteville, with whom she has co-authored multiple publications.
Metrics
- h-index: 2
- Publications: 2
- Citations: 16
Selected Publications
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Video-Based Autism Detection with Deep Learning (2024)
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The Effect of Response Conditions on Food Images-Evoked Emotions Measured Using the Valence × Arousal Circumplex-Inspired Emotion Questionnaire (CEQ) (2023)
Collaboration Network
Top Collaborators
- Video-Based Autism Detection with Deep Learning
- The Effect of Response Conditions on Food Images-Evoked Emotions Measured Using the Valence × Arousal Circumplex-Inspired Emotion Questionnaire (CEQ)
- The Effect of Response Conditions on Food Images-Evoked Emotions Measured Using the Valence × Arousal Circumplex-Inspired Emotion Questionnaire (CEQ)
- Video-Based Autism Detection with Deep Learning
- Video-Based Autism Detection with Deep Learning
- Video-Based Autism Detection with Deep Learning
- Video-Based Autism Detection with Deep Learning
- Video-Based Autism Detection with Deep Learning
- Video-Based Autism Detection with Deep Learning
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