Medical image segmentation has the priori guiding significance for clinical diagnosis and
treatment. In the past ten years, a large number of experimental facts have proved the great …

Classification of land use and land cover from remote sensing images has been widely used
in natural resources and urban information management. The variability and complex …

As one type of object detection, small object detection has been widely used in daily-life-
related applications with many real-time requirements, such as autopilot and navigation …

The haze weather environment leads to the deterioration of the visual effect of the image,
and it is difficult to carry out the work of the advanced vision task. Therefore, dehazing the …

With the rapid advancement of technology, satellite and drone technologies have had
significant impacts on various fields, creating both opportunities and challenges. In areas …

Remote sensing image dehazing is crucial for both military and civil applications. However,
dehazed remote sensing images often suffer from pronounced artifacts and tend to …

In complex natural haze scenes, image haze removal still faces significant challenges in
removing non-homogeneous and dense haze. The double complexity of haze distribution …

Plant diseases pose a significant threat to the economic viability of agriculture and the
normal functioning of trees in forests. Accurate detection and identification of plant diseases …

In recent years, the deep learning-based hyperspectral image (HSI) classification method
has achieved great success, and the convolutional neural network (CNN) method has …

This paper addresses the problem of blind deblurring of single remote sensing (RS) images
with deep neural networks. Most existing deep learning-based methods are migrated from …