Low-Budget Data Labeling

Do you want to know more about deciding which samples have to be prioritized for labeling in a new unseen dataset? Check our paper “Low-Budget Label Query through Domain Alignment Enforcement”, just published in the Computer Vision and Image Understanding journal.

In this work, we propose the new problem of low-budget label query, which aims at maximizing the classification performance by selecting a convenient and small set of samples (i.e., low budget) to be manually labeled from an arbitrary big set of unlabeled data.