基于深度学习的目标检测算法综述

A Survey of Object Detection Algorithms Based on Deep Learning

目标检测技术应用非常广泛,主要用于识别以及定位图像中的物体,是发展较快的一种技术。在广泛文献调研的基础上对大量检测算法进行了研究,对各种主流网络框架的结构、优缺点作出综述,从两阶段、一阶段两种范式对不同模型的原理、优点等进行了分析,对常用数据集进行了简单介绍,并对其未来发展趋势给出了合理的分析预测。

Target detection technology is widely used. It is mainly used to identify and locate objects in images. It is a rapidly developing technology. On the basis of extensive literature research, this paper studies a large number of detection algorithms,summarizes the structure, advantages and disadvantages of various mainstream network frameworks, analyzes the principles and advantages of different models from two-stage and one-stage paradigms, briefly introduces the common data sets, and gives a reasonable analysis and prediction of their future development trend.