首页> 外文会议>International Conference on Information Science and Communications Technologies >Estimation affects of formats and resizing process to the accuracy of convolutional neural network
【24h】

Estimation affects of formats and resizing process to the accuracy of convolutional neural network

机译:估计格式和大小调整过程对卷积神经网络准确性的影响

获取原文

摘要

image quality, formatting, resizing and compression processes affect on deep neural network performance. These affects are investigated in many papers. However, signal represented images do not look like images which were captured by a camera, because they were plotted in a computer, which let to omit some noises. So formatting and resizing processes are important parameters that affect on network accuracy. In this work, ECG signal representation in different domains were saved in different image formats and CNN trained on these images. Obtained results were compared and showed that JPG image format best fits for training ECG images on CNN.
机译:图像质量,格式,调整大小和压缩过程会影响深度神经网络的性能。这些影响已在许多论文中进行了研究。但是,信号表示的图像看起来不像是由相机捕获的图像,因为它们是在计算机中绘制的,因此可以忽略一些噪音。因此,格式化和调整大小的过程是影响网络准确性的重要参数。在这项工作中,以不同的图像格式保存了不同域中的ECG信号表示,并在这些图像上训练了CNN。比较获得的结果,结果表明JPG图像格式最适合在CNN上训练ECG图像。

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