Detecting objects using deep learning technology has the advantage of getting good
accuracy. The accuracy obtained depends on the processing time of using deep learning …

Object detection is the most fundamental and important task in computer vision. With the
development of hardware such as computing power of GPUs and cameras, object detection …

The current target detection models have the characteristics of large storage, large demand
for computing resources and large number of parameters, which are difficult to be …

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 …

Vehicle object detection is one of the important research directions in the field of computer
vision. Aiming at solving the problems of low accuracy, slow speed, and unsatisfactory …

Aiming at the problem of the large number of model parameters and poor performance on
the small-size object of the YOLOv2 object detection model, an improved YOLOv2 object …

Object detection is a challenging computer vision problem with numerous practical
applications. Due to low accuracy and slow detection speed in object detection, we propose …

You Only Look Once (YOLO) is an object detection system with real-time effects. It is difficult
to accurately detect small targets in complex scenes, so an improved network structure of …

Vehicle detection is the first step and an important part of automatic traffic incident detection
systems. It guarantees subsequent vehicle identification and vehicle counting accuracy and …

The detection of vehicles and pedestrians is driving ahead has been a hot topic in the field
of computer vision research. Although the current field of object detection developed rapidly …