The results indicate that block-level matching recognition substantially reduces misclassification compared to pixel-level methods, achieving over 60% accuracy across four study areas. The ...

The visual explainable active learning approach improves humans' efficiency of building zero-shot classification models interactively, compared with the method without guidance. We justify our results ...