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首页> 外文期刊>International Journal of Engineering Research and Applications >Artificial Intelligence Enabled Laser Fence System for Object Classification
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Artificial Intelligence Enabled Laser Fence System for Object Classification

机译：用于对象分类的人工智能启用激光栅栏系统

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摘要

In recent years, security of international borders and homeland have gained momentum. Country like India which has vast border line and is surrounded by many neighbourhood countries requires lot of infrastructure to cover the border by conventional means. Laser fence based network is gaining popularity worldwide. Smart sensor network is one of the potential solutions to protect the border areas. Some other sensors like thermal/day-night camera, underground seismic sensor, Passive Infra-Red sensors (PIR) etc. are also integrated with laser fence to enhance its efficacy during poor visibility conditions and different terrains. Other conditions like rain and atmospheric turbulence may be taken care of by adding ArtificialIntelligence (AI) to networked laser fence.As per published literature, current methodology is innovative as it classifies the real time object intrusion on the basis of temporal data fusion of multiple photo sensors. Velocity, length and height of an object are taken as key parameters to generate the data sets for object classification. In this methodology, multiple data sets for different real-time objects and for different terrains can be generated and stored to achieve better accuracy for classification of objects in human, vehicle and animal..
机译：近年来，国际边界​​和祖国的安全性势头。像印度一样的国家，拥有庞大的边界线，被许多社区各国包围需要大量的基础设施来通过传统方式覆盖边界。基于激光围栏的网络在全球范围内越来越受欢迎。智能传感器网络是保护边境地区的潜在解决方案之一。一些其他传感器，如热/天夜间相机，地下地震传感器，被动红外传感器（PIR）等也与激光围栏集成，以增强其在可见度条件和不同地形差的效率。如雨和大气湍流如雨和大气湍流可以通过向网络激光栅栏添加造型intelligence（AI）来处理。每种发布的文献，目前的方法是创新的，因为它根据多个照片的时间数据融合来分类实时对象侵扰传感器。对象的速度，长度和高度被视为键参数以生成用于对象分类的数据集。在该方法中，可以生成用于不同实时对象和不同地形的多个数据集，以实现人体，车辆和动物中对象的分类的更好准确性。

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