Abstract The Automated Model Evaluation (AutoEval) framework entertains the possibility of
evaluating a trained machine learning model without resorting to a labeled testing set …

Although the remote sensing (RS) community has begun to pretrain transformers (intended
to be fine-tuned on RS tasks), it is unclear how these models perform under distribution …

The performance of deep neural networks can vary substantially when evaluated on
datasets different from the training data. This presents a crucial challenge in evaluating …