1 citations · 1 across the 3 of their papers we have counts for
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Perceptual Quality-based Model Training under Annotator Label Uncertainty
Chen Zhou, Mohit Prabhushankar, Ghassan AlRegib
Annotators exhibit disagreement during data labeling, which can be termed as annotator label uncertainty. Annotator label uncertainty manifests in variations of labeling quality. T…
Learning Trajectory-Conditioned Relations to Predict Pedestrian Crossing Behavior
Chen Zhou, Ghassan AlRegib, Armin Parchami +1
In smart transportation, intelligent systems avoid potential collisions by predicting the intent of traffic agents, especially pedestrians. Pedestrian intent, defined as future act…
On the Ramifications of Human Label Uncertainty
Chen Zhou, Mohit Prabhushankar, Ghassan AlRegib
Humans exhibit disagreement during data labeling. We term this disagreement as human label uncertainty. In this work, we study the ramifications of human label uncertainty (HLU). O…
Augmented Bi-path Network for Few-shot Learning
Baoming Yan, Chen Zhou, Bo Zhao +5
Few-shot Learning (FSL) which aims to learn from few labeled training data is becoming a popular research topic, due to the expensive labeling cost in many real-world applications.…