Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …

Transformers have rapidly gained popularity in computer vision, especially in the field of
object recognition and detection. Upon examining the outcomes of state-of-the-art object …

Object detection is essential in the interpretation of remote sensing images (RSIs). However,
the blurred background and objects with vast variances are identified as the two main …

Recently, low-altitude remote sensing platforms are widely used for various practical
applications. Object detection is a basic and significant technology, serving them. The scale …

Remote sensing object detection (RSOD) encounters challenges in complex backgrounds
and small object detection, which are interconnected and unable to address separately. To …

Object detection plays a crucial role in scene understanding and has extensive practical
applications. In the field of remote sensing object detection, both detection accuracy and …

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 …

Detecting objects in remote sensing images (RSIs), characterized by dramatic scale
variation and complex backgrounds, has always been a challenging problem. These …

RGB–infrared object detection in remote-sensing images is crucial for achieving around-
clock surveillance of unmanned aerial vehicles. RGB–infrared remote-sensing object …

To address the problem of insufficient semantic feature information caused by small objects
in aerial images, an adaptive receptive field enhancement network based on attention …