In remote sensing (RS), multiple modalities of data are usually available, eg, RGB,
multispectral, hyperspectral, light detection and ranging (LiDAR), and synthetic aperture …

Current remote-sensing interpretation models often focus on a single task, such as
detection, segmentation, or caption. However, the task-specific designed models are …

In the wake of the rapid deployment of large-scale low-Earth orbit satellite constellations,
exploiting the full computing potential of Commercial Off-The-Shelf (COTS) devices in these …

The unique challenges of polar ecosystems, coupled with the necessity for high-precision
data, make Unmanned Aerial Vehicles (UAVs) an ideal tool for vegetation monitoring and …

Satellite remote sensing images contain complex and diverse ground object information and
the images exhibit spatial multi-scale characteristics, making the panoptic segmentation of …

Modern spacecraft are increasingly relying on machine learning (ML). However, physical
equipment in space is subject to various natural hazards, such as radiation, which may …

Remote sensing lightweight foundation models have successfully achieved online
perception, providing real-time intelligent interpretation. However, their capabilities are …

Remote sensing lightweight foundation models have achieved notable success in online
perception within remote sensing. However, their capabilities are restricted to performing …

Hand gesture recognition finds application in several heterogeneous fields, such as Human-
Computer Interaction, serious games, sign language interpretation, and more. Modern …

Hyperspectral imaging (HSI) captures spatial and spectral data, enabling analysis of
features invisible to conventional systems. The technology is vital in fields such as weather …