Object detection in remote sensing images (RSIs) requires the locating and classifying of
objects of interest, which is a hot topic in RSI analysis research. With the development of …

With practical applications such as environment surveillance, agricultural production, and
disaster assessment, accurate object detection in remote sensing images is in high demand …

Deep learning (DL)-based object detection algorithms have gained impressive
achievements in natural images and have gradually matured in recent years. However …

Remote sensing scene understanding is crucial for extracting valuable information from high-
resolution images, including object detection and classification. Traditional object detection …

The specific characteristics of remote sensing images, such as large directional variations,
large target sizes, and dense target distributions, make target detection a challenging task …

Automatic underwater target detection plays a vital role in sonar image processing and
analysis, and its core task is to discriminate target categories and achieve precise …

Forest fires are destructive and rapidly spreading, causing great harm to forest ecosystems
and humans. Deep learning techniques can adaptively learn and extract features of forest …

In the synthetic aperture radar (SAR) ship image, the target size is small and dense, the
background is complex and changeable, the ship target is difficult to distinguish from the …

Remote sensing technology has been modernized by artificial intelligence, which has made
it possible for deep learning algorithms to extract useful information from images. However …

In recent years, significant progress has been obtained in object detection using
Convolutional Neural Networks (CNNs). However, owing to the particularity of Remote …