land cover classification is one of the most important applications of polarimetric radar images, especially in urban areas. there are numerous features that can be extracted from these images for the use of their high potential, hence feature selection plays an important role in polsar image classification. in this study, three main steps are used to improve the classification: 1) feature extr...

Abstract Even though numerous works focus on the few-shot learning issue by combining meta-learning, there are still limits to traditional graph classification problems. The antecedent algorithms directly extract features from samples, and do not take into account preference of trained model previously “seen” targets. In order overcome aforementioned issues, an effective strategy with training ...