机电工程技术2024，Vol.53Issue(8)：7-12,6.DOI:10.3969/j.issn.1009-9492.2024.08.002
Anchor-free目标检测算法综述
Overview of Anchor-free Object Detection Algorithms
陈恒星 1刘一鸣2
作者信息
- 1. 澳门科技大学商学院,澳门 999078
- 2. 中山大学管理学院,广州 510006
- 折叠
摘要
Abstract
As the foundation of computer vision,object detection is of great significance to the development of artificial intelligence.For a long time,many scholars are committed to improve the efficiency and performance of object detection algorithms.Due to the advantages of flexible scale and strong robustness,deep learning algorithms of anchor-free object detection gradually are widely used in object detection.Convolutional neural network and Transformer,as the classical network architectures in the field of object detection,are introduced.Based on the core network architecture as the classification standard,the anchor-free object detection deep learning algorithms are introduced based on convolutional neural network and Transformer,respectively.The improvements,advantages and disadvantages of these algorithms are summarized,the future development and application of this direction are anticipated.关键词
目标检测/anchor-free/卷积神经网络/TransformerKey words
object detection/anchor-free/convolutional neural network/Transformer分类
信息技术与安全科学引用本文复制引用
陈恒星,刘一鸣..Anchor-free目标检测算法综述[J].机电工程技术,2024,53(8):7-12,6.
