Ship detection from synthetic aperture radar (SAR) remote sensing images is essential for
monitoring water traffic and marine safety. Numerous methods for ship detection have been …

In existing superpixel-wise saliency detection algorithms, superpixel generation often is an
isolated preprocessing step. The performance of saliency maps is determined by the …

The diagram kind of a graph is used to show accumulated data. Graphs can be utilized for a
variety of purposes because this data can be either quantitative or qualitative. Graphs can …

Few-shot object detection (FSOD) has received numerous attention due to the difficulty and
time-consuming of labeling objects. Recent researches achieve excellent performance in a …

In this research draft, by keeping in view, the importance of Zagreb numbers, first we defined
some familiar graph families and their degrees in fuzzy soft environment, and then by …

Oil spills have proven to have detrimental effects on the marine-based environment and
economy. Thus, it is necessary to identify oil spills and classify them in the sea to reduce oil …

Synthetic aperture radar (SAR) systems have the capacity for day-and-night and all-weather
surveillance, which has become increasingly indispensable for military surveillance and …

Remarkable progress based on deep neural networks has been achieved in the semantic
segmentation of remote sensing images (RSIs). However, pixel-level labeling is expensive …

Convolutional Neural Network (CNN) has been widely applied in the field of synthetic
aperture radar (SAR) image recognition. Nevertheless, CNN-based recognition methods …

Semantic segmentation, a fundamental research direction in synthetic aperture radar (SAR)
image interpretation, has significant application value for multiple sectors. However, noise …