After the revival of deep learning in computer vision in 2012, SAR ship detection comes into
the deep learning era too. The deep learning-based computer vision algorithms can work in …

Within the next several years, there will be a high level of autonomous technology that will
be available for widespread use, which will reduce labor costs, increase safety, save energy …

Coconut (Cocos nucifera L.) is one of the world's most economically important tree species,
and coconut palm plantations dominate many islands and tropical coastlines. However, the …

Ship detection in synthetic aperture radar (SAR) images is a significant and challenging
task. However, most existing deep learning-based SAR ship detection approaches are …

Most of the existing synthetic aperture radar (SAR) ship instance segmentation models do
not achieve mask interaction or offer limited interaction performance. Besides, their …

Existing instance segmentation models mostly pay less attention to the targeted
characteristics of ships in synthetic aperture radar (SAR) images, which hinders further …

Convolutional neural networks (CNNs) have been widely applied in the context of ship
detection in synthetic aperture radar (SAR) images, but the detection performance is still not …

Fast and high-accuracy detection of underwater targets based on side scan sonar images
has great potential for marine fisheries, underwater security, marine mapping, underwater …

This paper presents a novel approach to tracking ships in Synthetic Aperture Radar (SAR)
images based on an improved lightweight YOLOv8 Nano (YOLOv8n), specially devised to …

In this paper, we propose a localization method applicable to 3D LiDAR by improving the
LiDAR localization algorithm, such as AMCL (Adaptive Monte Carlo Localization). The …