Given the large volume of remote sensing images collected daily, automatic object detection
and segmentation have been a consistent need in Earth observation (EO). However, objects …

Leveraging the extensive training data from SA-1B, the segment anything model (SAM)
demonstrates remarkable generalization and zero-shot capabilities. However, as a category …

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 …

Existing deep learning (DL)-based synthetic aperture radar (SAR) ship instance
segmentation models mostly extract feature subsets at the single level of feature pyramid …

The object detection of unmanned aerial vehicle (UAV) images has widespread applications
in numerous fields; however, the complex background, diverse scales, and uneven …

The reliable and efficient large-scale map** of date palm trees from remotely sensed data
is crucial for develo** palm tree inventories, continuous monitoring, vulnerability …

Detecting and tracking ships remotely is now required in a wide range of contexts, from
military security to illegal immigration control, as well as the management of fisheries and …

Marine ships are the transport vehicle in the ocean and instance segmentation of marine
ships is an accurate and efficient analysis approach to achieve a quantitative understanding …

The segment anything model (SAM), a foundational model designed for promptable
segmentation tasks, demonstrates exceptional generalization capabilities, making it highly …