首页> 外文会议>Intelligent Robots and Computer Vision X: Neural, Biological, and 3-D Methods >Hybrid ANN-ES architecture for automatic target recognition
【24h】

Hybrid ANN-ES architecture for automatic target recognition

机译:混合式ANN-ES架构,可自动识别目标

获取原文
获取原文并翻译 | 示例

摘要

Abstract: Automatic target recognition can benefit from cooperation of artificial neural networks (ANNs) and expert systems (ESs). Bottom-up training and generalization properties of artificial neural networks, and top-down utilization of accumulated knowledge by expert system processors, can be combined to offer robust performance of the automatic target recognition models. In this paper, we propose a modular, flexible and expandable, hybrid architecture which provides cooperative, functional and operational interfaces between expert system and artificial neural networks facilities. In order to make the problem more specific, we apply this architecture to the Multline Optical Character Reader (MLOCR) system, which is being developed to sort the postal mail pieces automatically.!19
机译:摘要:自动目标识别可以受益于人工神经网络(ANN)和专家系统(ES)的合作。可以组合使用人工神经网络的自下而上的训练和通用属性,以及专家系统处理器自上而下的累积知识利用,以提供自动目标识别模型的强大性能。在本文中,我们提出了一种模块化,灵活且可扩展的混合体系结构,该体系结构提供了专家系统与人工神经网络设施之间的协作,功能和操作接口。为了使问题更具体,我们将此体系结构应用于Multline光学字符读取器(MLOCR)系统,该系统正在开发中,可以自动对邮政邮件进行分类。!19

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号