← Search

Islam Nassar

2 accepted papers

2023

ProtoCon: Pseudo-Label Refinement via Online Clustering and Prototypical Consistency for Efficient Semi-Supervised Learning

CVPR 2023highlight

Confidence-based pseudo-labeling is among the dominant approaches in semi-supervised learning (SSL). It relies on including high-confidence predictions made on unlabeled data as additional targets to train the model. We propose ProtoCon, a novel SSL method aimed at the less-explored label-scarce SSL…

Cited by 29SourcePDFScholar
2021

All Labels Are Not Created Equal: Enhancing Semi-Supervision via Label Grouping and Co-Training

CVPR 2021poster

Pseudo-labeling is a key component in semi-supervised learning (SSL). It relies on iteratively using the model to generate artificial labels for the unlabeled data to train against. A common property among its various methods is that they only rely on the model's prediction to make labeling decision…

Cited by 71PDFcodeScholar