计算机工程与应用 ›› 2022, Vol. 58 ›› Issue (24): 12-28.DOI: 10.3778/j.issn.1002-8331.2206-0139
韩晶晶,刘江越,公维军,魏宏杨,钱育蓉
出版日期:
2022-12-15
发布日期:
2022-12-15
HAN Jingjing, LIU Jiangyue, GONG Weijun, WEI Hongyang, QIAN Yurong
Online:
2022-12-15
Published:
2022-12-15
摘要: 为适应移动智能时代对实时目标检测的需求,人们针对面向移动端的目标检测优化问题提出了众多解决思路。其优化思路可归纳为轻量化网络设计和模型压缩两类:一类是基于手工设计或自动化机器学习(AutoML)手段,在网络设计之初就采用轻量化卷积设计构建轻量化网络;另一类是借助张量分解、模型剪枝、参数量化等压缩手段,调整现有的目标检测模型来优化检测性能。考虑到优化方法的发展规律不尽相同且彼此之间有所关联,分别采取了不同的分析角度和对比维度。从市场角度剖析了国内面向移动端的目标检测产业化现状,并对其优化研究的潜在问题和发展方向进行了总结与展望。
韩晶晶, 刘江越, 公维军, 魏宏杨, 钱育蓉. 面向移动端的目标检测优化研究[J]. 计算机工程与应用, 2022, 58(24): 12-28.
HAN Jingjing, LIU Jiangyue, GONG Weijun, WEI Hongyang, QIAN Yurong. Object Detection Optimization Research for Mobile Terminals[J]. Computer Engineering and Applications, 2022, 58(24): 12-28.
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