AI Research
Effects of Deep Learning Architecture and Pretraining on Automated Vocal Fold Segmentation in Ex Vivo High-Speed Phonation Images
A study examines deep-learning choices for segmenting vocal folds in high-speed images
Two-dimensional (2D) intraglottal particle image velocimetry (PIV) of ex vivo phonation experiments quantifies vocal fold medial surface dynamics and the intraglottal flow field.
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ArXiv CS.CV
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2 min
ArXiv CS.CV
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Automated segmentation can support analysis of vocal fold motion and airflow in ex vivo phonation experiments. Comparing architectures and pretraining may help clarify how these choices affect that image-analysis task.
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