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 …

Ship detection and classification pose significant challenges in remote sensing. The potent
feature extraction capabilities of deep learning algorithms render them pivotal for these …

With the development of synthetic aperture radar (SAR) imaging and deep learning, SAR
ship detection based on convolutional neural networks (CNNs) has been extensively …

Remote sensing ship recognition is widely used in civil and military applications, such as
national defense construction, fishery management, and navigation supervision …

Ship detection aims to automatically identify whether there are ships in the images, precisely
classifies and localizes them. Regardless of whether utilizing early manually designed …

Ship detection has broad applications in many areas, including fishery management,
maritime rescue, and maritime monitoring. Recently, numerous detectors based on deep …

A synthetic aperture radar (SAR) has the characteristics of all-weather and all-time
operation, which can achieve uninterrupted detection of targets on the sea surface …

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

One of the current research areas in the synthetic aperture radar (SAR) processing fields is
deep learning-based ship detection in SAR imagery. Recently, ship detection in SAR …

Ships comprise the only and most important ocean transportation mode. Thus, ship
detection is one of the most critical technologies in ship monitoring, which plays an essential …