Search Results for author:
Found 2 papers, 0 papers with code
Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification
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.
Mixup-based Deep Metric Learning Approaches for Incomplete Supervision
Deep learning architectures have achieved promising results in different areas (e. g., medicine, agriculture, and security).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
