Detecting small or tiny objects is always a difficult and challenging issue in computer vision.
In this paper, we provide a latest and comprehensive survey of deep learning-based …

The capabilities of autonomous mobile robotic systems have been steadily improving due to
recent advancements in computer science, engineering, and related disciplines such as …

With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …

Object detection is the most important problem in computer vision tasks. After AlexNet
proposed, based on Convolutional Neural Network (CNN) methods have become …

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 …

Abstract Unmanned Aerial Vehicle (UAV) aerial photography object detection has high
research significance in the fields of disaster rescue, ecological environmental protection …

Object detection is crucial in aerial imagery analysis. Previous methods based on
convolutional neural networks (CNNs) require large-scale labeled datasets for training to …

Autonomous driving is a promising way to future safe, efficient, and low-carbon
transportation. Real-time accurate target detection is an essential precondition for the …

The loss of infrared dim-small target features in the network sampling process is a major
factor affecting its detection accuracy. In order to reduce this loss, this paper proposes YOLO …

The need for pedestrian target detection in uncrewed aerial vehicle (UAV) remote sensing
images has become increasingly significant as the technology continues to evolve. UAVs …