The development of computer vision algorithms for Unmanned Aerial Vehicles (UAVs)
imagery heavily relies on the availability of annotated high-resolution aerial data. However …

The detection of infrared vehicle targets by UAVs poses significant challenges in the
presence of complex ground backgrounds, high target density, and a large proportion of …

Multimodal large language models (MLLMs) have demonstrated remarkable success in
vision and visual-language tasks within the natural image domain. Owing to the significant …

In recent years, the combination of artificial intelligence (AI) and unmanned aerial vehicles
(UAVs) has brought about advancements in various areas. This comprehensive analysis …

Owing to the significant application potential of unmanned aerial vehicles (UAVs) and
infrared imaging technologies, researchers from different fields have conducted numerous …

With the rapid development of UAV and infrared imaging technology, the cost of UAV
infrared imaging technology has decreased steadily. Small target detection technology in …

In the context of small unmanned aerial vehicles (UAVs), infrared imaging faces challenges
such as low quality, difficulty in detecting small targets, high false alarm rates, and …

Conducting extensive vehicle detection through the high-altitude perspective offered by
Unmanned Aerial Vehicle (UAV) poses significant challenges. The high-altitude operation of …

Generative adversarial networks (GANs) have achieved remarkable progress in the natural
image field. However, when applying GANs in the remote sensing (RS) image generation …

To address the issues of low model accuracy caused by complex ground environments and
uneven target scales and high computational complexity in unmanned aerial vehicle (UAV) …