摘要
当前计算机视觉领域的研究热点之一是目标检测,其根本是对图像中指定目标的识别。而深度学习是目前发展快速、应用广泛的一种技术,其具备的学习能力可以在目标检测中对目标进行图像识别、特征提取以及分类识别等操作。通过介绍深度学习的研究进展,分析了各种网络模型的特点;最后总结了深度学习在目标检测领域的应用发展,结合当前问题和挑战,分析了今后的研究发展。
Nowadays,one of the research focuses in the field of computer vision is target detection,which aims at identifying and detecting the designated targets in images.At present,deep learning is a technology with rapid development and wide application range,and its learning ability can perform image recognition,feature extraction,classification recognition and other operations in target detection.The research progress of deep learning was mainly introduced.The characteristics of various network models were analyzed.Finally,the application development of deep learning in the field of target detection was expounded,and the future research development is combined with the current problems and challenges was analyzed.
作者
赵立新
邢润哲
白银光
张宏昌
何春燕
ZHAO Li-xin;XING Run-zhe;BAI Yin-guang;ZHANG Hong-chang;HE Chun-yan(School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056000)
出处
《科学技术与工程》
北大核心
2021年第30期12787-12795,共9页
Science Technology and Engineering
基金
河北高领冶金技术科技公司支撑项目(HK2020000248)。
关键词
深度学习
计算机视觉
目标检测
特征提取
deep learning
computer vision
target detection
feature extraction
