In view of the poor accuracy of mainstream object detection algorithms in detecting tiny
objects, A tiny object detection algorithm based on improved YOLOv5 is proposed. The main …

In object detection tasks, Frontier small object detection algorithms basically suffer from low
accuracy in detecting small objects. Given this situation, we propose the lightweight YOLOv5 …

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 …

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 …

Small object detection is one of the challenging tasks in computer vision. Most of the existing
small object detection models cannot fully extract the characteristics of small objects within …

In recent years, many deep learning-based object detection methods have performed well in
various applications, especially in large-scale object detection. However, when detecting …

With the development of computer vision, small object detection has become a research
pain point and difficulty in computer vision. Feature acquisition and accurate localization of …

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 …

In the research of computer vision, a very challenging problem is the detection of small
objects. The existing detection algorithms often focus on detecting full-scale objects, without …

Small target detection is a very difficult task and remains one of the most challenging
problems in computer vision due to variations in object shape, appearance and position, as …