首页> 外文会议>Distributed computing and artificial intelligence >Classification of Fatigue Bills Based on K-Means by Using Creases Feature
【24h】

Classification of Fatigue Bills Based on K-Means by Using Creases Feature

机译:基于折痕特征的K均值疲劳账单分类

获取原文
获取原文并翻译 | 示例

摘要

The bills in circulation generate a large amount of fatigue bills every year, causing various types of problems, such as the paper jam in automatic tellers due to overwork and exhaustion. A highly advanced bill classification technique, which distinguishes whether a bill is a reusable bill specifying the level of fatigue, is greatly required in order to comb out these problematic bills. Therefore, a purpose of this paper is to suggest a classification method of fatigue bills based on K-means with bill image data. The effectiveness of this approach is verified by the bill discriminant experimentation.
机译:流通中的钞票每年都会产生大量的疲劳钞票,从而引起各种类型的问题,例如由于过度工作和精疲力尽而导致自动柜员机卡纸。为了梳理这些有问题的钞票,非常需要一种先进的钞票分类技术,该技术区分钞票是否为指定疲劳程度的可重复使用的钞票。因此,本文的目的是提出一种基于带有票据图像数据的K均值的疲劳票据分类方法。票据判别实验验证了这种方法的有效性。

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