Objective. Computer vision-based up-to-date accurate damage classification and
localization are of decisive importance for infrastructure monitoring, safety, and the …

With the accelerated development of artificial intelligence, remote-sensing image
technologies have gained widespread attention in smart cities. In recent years, remote …

Remote sensing object detection (RSOD), one of the most fundamental and challenging
tasks in the remote sensing field, has received long-standing attention. In recent years, deep …

Aiming at the problem of a large number of small dense objects in high-altitude shooting and
complex background noise interference in the captured scenes, an improved object …

Weeds in the field affect the normal growth of lettuce crops by competing with them for
resources such as water and sunlight. The increasing costs of weed management and …

This paper presents a deep learning-based approach for multiclass surface damage
detection and segmentation in various bridge components. The proposed BridgeNet …

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 …

Drone detection is a significant research topic due to the potential security threats posed by
the misuse of drones in both civilian and military domains. However, traditional drone …

Deep learning (DL)-based object detection algorithms have gained impressive
achievements in natural images and have gradually matured in recent years. However …

This study aimed to address the problems of low detection accuracy and inaccurate
positioning of small-object detection in remote sensing images. An improved architecture …