English: We start with a small dataset of labeled images. We then train a classifier on this data. The active learning process then uses the current classifier to select a handful of unlabeled images that are likely to improve classifier performance. Finally, humans produce labels for these images, adding them to the labeled dataset. The process can be repeated to iteratively improve the classifier’s performance.