Remote sensing image scene classification with deep learning (DL) is a rapidly growing
field that has gained significant attention in the past few years. While previous review papers …

Accurate spatial information on Land use and land cover (LULC) plays a crucial role in city
planning. A widely used method of obtaining accurate LULC maps is a classification of the …

Object Classification in Remote Sensing Imagery holds paramount importance for extracting
meaningful insights from complex aerial scenes. Conventional methods encounter …

Semantic segmentation has been widely used in precision agriculture, such as weed
detection, which is pivotal to increasing crop yields. Various well-established and swiftly …

Underwater target detection technology plays a crucial role in the autonomous exploration of
underwater vehicles. In recent years, significant progress has been made in the field of …

Most existing scene classification methods based on remote sensing images tend to ignore
important interactive information at different levels in the image. We propose an effective …

The advancement in satellite image sensors has enabled the acquisition of high-resolution
remote sensing (HRRS) images. However, interpreting these images accurately and …

Accurate information retrieval from multi-source and multi-resolution image data constitutes
a foundation for knowledge discovery. Scene image classification in the remote sensing …

Classification of very high-resolution (VHR) aerial remote sensing (RS) images is a well-
established research area in the RS community as it provides valuable spatial information …

Remote sensing images exhibit significant variations in target scale and complex
backgrounds, as well as distinct differences within classes and high similarities between …