Detection of small targets in aerial images is still a difficult problem due to the low resolution
and background-like targets. With the recent development of object detection technology …

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 for street-level objects can be applied to various use cases, from car and
traffic detection to the self-driving car system. Therefore, finding the best object detection …

Small object detection has important application value in the fields of autonomous driving
and drone scene analysis. As one of the most advanced object detection algorithms …

According to the problem that the multi-scale vehicle objects in traffic surveillance video are
difficult to detect and the overlapping objects are prone to missed detection, an improved …

In this paper, an improved algorithm based on Yolo V3 is proposed, which can effectively
improve the accuracy of small target detection. First of all, the feature map acquisition …

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 …

Most of the mainstream object detectors are unable to handle the problem of small object
detection. Therefore, we proposed a small target deep convolution recognition algorithm …

Convolutional neural networks (CNNs) have shown strong learning capabilities in computer
vision tasks such as classification and detection. Especially with the introduction of excellent …