Image classification has always been a hot research direction in the world, and the
emergence of deep learning has promoted the development of this field. Convolutional …

Deep learning-based algorithms have seen a massive popularity in different areas of remote
sensing image analysis over the past decade. Recently, transformer-based architectures …

Remote sensing image scene classification, which aims at labeling remote sensing images
with a set of semantic categories based on their contents, has broad applications in a range …

Scene classification is a highly useful task in Remote Sensing (RS) applications. Many
efforts have been made to improve the accuracy of RS scene classification. Scene …

Remote sensing image scene classification is an active and challenging task driven by
many applications. More recently, with the advances of deep learning models especially …

Remote sensing image scene classification is one of the most challenging problems in
understanding high-resolution remote sensing images. Deep learning techniques …

Few-shot image classification has attracted extensive attention, which aims to recognize
unseen classes given only a few labeled samples. Due to the large intraclass variances and …

Most of the existing deep-learning-based methods are difficult to effectively deal with the
challenges faced for geospatial object detection such as rotation variations and appearance …

Remote sensing scene classification (RSSC) is a hotspot and play very important role in the
field of remote sensing image interpretation in recent years. With the recent development of …

Scene classification of high spatial resolution (HSR) images can provide data support for
many practical applications, such as land planning and utilization, and it has been a crucial …