Several authors rely on transfer learning from pretrained models, arguing that using well-known datasets, which are available on the internet (e.g. ImageNet) their model will be able to handle a specific problem with a reduced training step.

In Remote Sensing this perspective is also becoming a trend when using Deep Learning techniques to classify Remote Sensing datasets.

In my opinion, the datasets used for pretrain are very different from Remote Sensing targets, mainly in two aspects:

If you agree, or if you do not agree, please give some feedback and let's learn together.

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