1 citations · 1 across the 1 of their papers we have counts for
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Class-Balanced Active Learning for Image Classification
Javad Zolfaghari Bengar, Joost van de Weijer, Laura Lopez Fuentes +1
Active learning aims to reduce the labeling effort that is required to train algorithms by learning an acquisition function selecting the most relevant data for which a label shoul…
Reducing Label Effort: Self-Supervised meets Active Learning
Javad Zolfaghari Bengar, Joost van de Weijer, Bartlomiej Twardowski +1
Active learning is a paradigm aimed at reducing the annotation effort by training the model on actively selected informative and/or representative samples. Another paradigm to redu…
Temporal Coherence for Active Learning in Videos
Javad Zolfaghari Bengar, Abel Gonzalez-Garcia, Gabriel Villalonga +5
Autonomous driving systems require huge amounts of data to train. Manual annotation of this data is time-consuming and prohibitively expensive since it involves human resources. Th…