首页> 外文会议>International Symposium on Advanced Intelligent Systems;International Conference on Soft Computing and Intelligent Systems >A Pattern Recognition Method for Scene Sketch Images Using Deep Learning and Its Evaluation
【24h】

A Pattern Recognition Method for Scene Sketch Images Using Deep Learning and Its Evaluation

机译:使用深度学习的场景草图图像的模式识别方法及评价

获取原文

摘要

Many studies on handwritten figure recognition have been published so far. For handwritten graphics in the fields of science and engineering, clear drawing rules are often clear, that is the shapes of the elements are predetermined. On the other hand, there is no drawing rule for sketches such as scene sketches; this makes it difficult to design a feature extractor. Based on this background, in recent years, research on recognition models using deep learning for sketch images has been reported. However, the recognition rate of all the previous research results are about 70% or less. Therefore, in this paper, we propose a new CNN model for recognizing landscape sketch images, and verify its effectiveness by computer experiments. Since there is no benchmark data for landscape sketch images, it cannot be compared with the results of previous studies, but the recognition rate of the CNN model proposed here is about 80%, which is higher than that of previous studies.
机译:到目前为止已经发布了关于手写的人写识别的许多研究。对于科学和工程领域的手写图形,清晰的绘图规则通常很清楚,即元素的形状是预先确定的。另一方面,诸如场景草图的草图没有绘图规则;这使得设计特征提取器难以设计。基于这一背景,近年来,已经报道了对使用深度学习进行草图图像的识别模型的研究。然而,所有以前研究结果的识别率约为70%或更低。因此,在本文中,我们提出了一种新的CNN模型,用于识别景观草图图像,并通过计算机实验验证其有效性。由于没有景观草图图像的基准数据,因此不能与先前研究的结果进行比较,但这里提出的CNN模型的识别率约为80%,其高于先前研究的80%。

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