Object detection is a fundamental and impactful area of exploration in computer vision and
video processing, with wide-ranging applications across diverse domains. The advent of the …

Object detection is of significant importance in the field of computer vision, since it has
extensive applications across many sectors. The emergence of YOLO (You Only Look Once) …

The utilization of deep learning technology for object detection offers the notable benefit of
attaining high levels of accuracy. The level of accuracy attained is contingent upon the …

In recent years, the You Only Look Once (YOLO) series of object detection algorithms have
garnered significant attention for their speed and accuracy in real-time applications. This …

The aim of the proposed work is to detect multiple objects effectively of different classes
using YOLOv3-320 in comparison with YOLOv3-tiny algorithm. A sample size of 91 acquired …

YOLOv5 is an algorithm with good performance in single-stage target detection at present,
but the accuracy of target boundary regression is not too high, so it is difficult to apply to …

This paper focuses on the performance optimization and application of the YOLOv8 model in
object detection. Firstly, the model architecture and optimization strategies of YOLOv8 are …

Object detection based on deep learning has made great progress in the past decade and
has been widely used in various fields of daily life. Model lightweighting is the core of …

Abstract The You Only Look Once (YOLO) algorithm has revolutionized object detection in
computer vision. YOLOv8 is the latest iteration of this algorithm, which builds on the …

Aiming at the problem of small object miss detection in object detection process, an
improved YOLOv5 (You Only Look Once) object detection algorithm based on attention …