基于深度学习的无锚框目标检测算法综述

近年来，基于深度学习的无锚框目标检测算法备受关注。为了深入理解无锚框检测算法，对比分析了基于深度学习的无锚框检测算法的原理机制、网络结构、核心特性以及优缺点，归纳总结了无锚框检测算法的核心技术，并在同一数据集上通过性能实验研究上述算法的性能，总结提出基于深度学习的目标检测算法未来的研究方向。

Overview of Anchor-Free Object Detection Algorithms Based on Depth Learning

In recent years,target detection algorithm based on deep learning has attracted much attention.In order to deeply understand the typical anchor-free object detection algorithms,the principle mechanism,network structure,core characteristics,advantages and disadvantages of seven anchor-free object detection algorithms based on deep learning were compared and analyzed.The performance of the above algorithms was experimentally studied.On this basis,the main characteristics of the anchor-free object detection algorithm were summarized,and the research direction of the anchor-free object detection algorithm was pointed out.