Object detection is an important basis for understanding the high-level semantic information
of images. To address the problems of small object accuracy and inaccurate bounding box …

In deep learning, object detection has achieved a very large performance improvement.
However, due to the few features available for small objects, network structure, sample …

Research on object detection algorithms with higher accuracy and faster detection speed is
currently the main concern. In order to improve detection performance, an improved object …

In recent years, the existing target detection algorithms have difficulties in detecting small
targets, such as low target resolution, large interference in complex scenes, and lack of large …

Object detection remains a vital yet challenging task in the domain of computer vision.
Despite high-performance computers delivering satisfactory results, existing methods …

Object detection is one of the most important and challenging branches in computer vision.
Although impressive progress have been achieved on large or medium scale objects …

To solve the problems of the existing object detection algorithms, such as insufficient feature
extraction ability and slow detection speed, we propose a object detection algorithm which …

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 …

Traditional YOLOv4 object detection network is difficult to be applied to mobile embedded
devices because it has some deficiencies such as complex structure and too many …

Object detection, a crucial aspect of computer vision, has seen significant advancements in
accuracy and robustness. Despite these advancements, practical applications still face …