As a special type of transformer, vision transformers (ViTs) can be used for various computer
vision (CV) applications. Convolutional neural networks (CNNs) have several potential …

Detecting drones in a video is a challenging problem due to their dynamic movements and
varying range of scales. Moreover, since drone detection is often required for security, it …

It is uncertain whether the power of transformer architectures can complement existing
convolutional neural networks. A few recent attempts have combined convolution with …

The increasing prevalence of unmanned aerial vehicles (UAVs), commonly known as
drones, has generated a demand for reliable detection systems. The inappropriate use of …

With the continuous development of autonomous driving, real-time target detection has
become increasingly critical in autonomous driving systems. However, traditional target …

The detection of small infrared targets with low signal-to-noise ratio (SNR) and low contrast
in high-noise backgrounds is challenging due to the lack of spatial features of the targets …

With the continuous advancement of drone technology, drones are demonstrating a trend
toward autonomy and clustering. The detection of airborne objects from the perspective of …

With the rapid development of science and technology, uncrewed aerial vehicle (UAV)
technology has shown a wide range of application prospects in various fields. The accuracy …

Under the advancement of artificial intelligence, Unmanned Aerial Vehicles (UAVs) exhibit
efficient flexibility in military reconnaissance, traffic monitoring, and crop analysis. However …

Detecting objects autonomously from a drone camera presents significant challenges. One
major obstacle is the lack of an adequate dataset in terms of both quantity and diversity …