Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification

arXiv:2303.11389v2 Announce Type: replace-cross
Abstract: Aerial scene classification, which aims to semantically label remote sensing images in a set of predefined classes (e.g., agricultural, beach, and harbor), is a very challenging task in remote sensing due to high intra-class variability and the different scales and orientations of the objects present in the dataset images. In remote sensing area, the use of CNN architectures as an alternative solution is also a reality for scene classification tasks. Generally, these CNNs are used …

abstract aerial arxiv class classification classifiers cs.cv cs.lg images objects sensing set through type