20 citations · 41 across the 6 of their papers we have counts for
4 papers · 1 filter
Exploiting and Guiding User Interaction in Interactive Machine Teaching
Zhongyi Zhou
Humans are talented with the ability to perform diverse interactions in the teaching process. However, when humans want to teach AI, existing interactive systems only allow humans…
Gesture-aware Interactive Machine Teaching with In-situ Object Annotations
Zhongyi Zhou, Koji Yatani
Interactive Machine Teaching (IMT) systems allow non-experts to easily create Machine Learning (ML) models. However, existing vision-based IMT systems either ignore annotations on…
Enhancing Model Assessment in Vision-based Interactive Machine Teaching through Real-time Saliency Map Visualization
Zhongyi Zhou, Koji Yatani
Interactive Machine Teaching systems allow users to create customized machine learning models through an iterative process of user-guided training and model assessment. They primar…
SyncUp: Vision-based Practice Support for Synchronized Dancing
Zhongyi Zhou, Anran Xu, Koji Yatani
The beauty of synchronized dancing lies in the synchronization of body movements among multiple dancers. While dancers utilize camera recordings for their practice, standard video…