摘要
针对当前人工智能技术在军用领域的应用问题和难点,研究基于深度学习技术的军用软硬件架构设计方法,并且结合业内主流的软硬件基础架构,分析在军事应用中涉及的关键技术和解决思路。通过对深度学习模型压缩转化、数据增强和分布式训练等软硬件架构的关键技术研究,设计构建了一站式人工智能开发平台、嵌入式边缘智能计算平台,对军用人工智能提供端到端的训练、部署和测试支撑。该研究可为未来智能无人作战系统提供软硬协同的智能计算解决方案。
Aiming at the application problems and difficulties of artificial intelligence technology in the military field,the design method of military hardware and software architecture based on deep learning technology is studied.Combined with the mainstream software and hardware infrastructure in the industry,the key technologies and solutions in military applications are analyzed.Through studying the key technologies of software and hardware architecture,including deep learning model compression transformation,data enhancement and distributed training,this paper designs and builds a one-stop artificial intelligence development platform and an embedded edge intelligent computing platform to provide end to end training,department and test support for military AI.It provides a software-hardware collaborative intelligent computing solution for future intelligent unmanned combat system.
作者
杨建
傅明驹
徐国强
Yang Jian;Fu Mingju;Xu Guoqiang(BU of Computer,Jiangsu Automation Research Institute,Lianyungang 222000,China)
出处
《信息技术与网络安全》
2020年第3期44-49,共6页
Information Technology and Network Security
基金
国防预研课题(31511040102)
关键词
军用人工智能
模型压缩
数据增强
一站式人工智能开发平台
嵌入式边缘智能计算平台
military artificial intelligence
model compression
data enhancement
one-stop artificial intelligence development platform
embedded edge intelligent computing platform
