Due to the complex and highly heterogeneous land cover in urban areas, the single-
temporal pixel-wise and parcel-wise classification cannot realize high-precision recognition …

Industrial inspection is crucial for maintaining quality and safety in industrial processes.
Deep learning models have recently demonstrated promising results in such tasks. This …

To address the issue of low detection accuracy caused by low illumination and occlusion in
underground coal mines, this study proposes an innovative miner detection method. A large …

The use of pretrained models from general computer vision tasks is widespread in remote
sensing, significantly reducing training costs and improving performance. However, this …

Object or Target identification has perennially represented a focal point of investigation
within the realm of computer vision; particularly the task of detection in satellite imagery has …

The advent of sensor technologies has led to the sheer amount volume of remote sensing
data containing fruitful spatial and spectral information. Insights into Earth's surface's objects …

Lightweight target detection algorithms are crucial for real-time processing of remote
sensing satellite images. However, due to the large size of remote sensing images and high …

Detecting objects in remote sensing images (RSIs) is essential for various applications, from
urban planning to disaster response. However, current deep learning models often struggle …

CCRS, distinguished by its substantial storage capacity, ro-bust high-performance
computing capabilities, and the flexible, on-demand elastic expansion service model, offers …