The characteristics of synthetic aperture radar (SAR) images are easily affected by factors
such as sensor parameters, imaging scenes, etc., which may lead to data distributional …

In the detection of surface floating garbage, the existence of complex backgrounds and the
small target sizes make the surface floating garbage easy to mis-detect. Existing approaches …

Ship detection in synthetic aperture radar (SAR) images is critical to ocean surveillance and
rescue. Although many deep learning SAR ship detection methods have been proposed, the …

The problem of multiscale ship detection in synthetic aperture radar (SAR) images has
received much attention with the development of deep convolutional neural networks …

A single sensor radar can no longer satisfy the increasingly complex electromagnetic
environment. More attention is paid to radar sensor networks, which can obtain more …

Synthetic aperture radar (SAR) can provide high-resolution and large-scale maritime
monitoring, which is beneficial to ship detection. However, ship-detection performance is …

Recently, convolution neural networks (CNNs) have been extensively utilized in synthetic
aperture radar (SAR) ship detection owing to their strong feature extraction and …

To improve target detection performance in SAR images, the YOLOV5 network is modified at
four different parts, including the input, backbone, neck, and head modules. At the input end …

Книга посвящена решению теоретических и практических проблем обнаружения,
измерения параметров и классификации пространственно-распределённых целей …

Аннотация Проблема синтеза и анализа алгоритмов обработки радиолокационных
изображений пространственно-распределенных целей, полученных средствами …