• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Robot Intelligence Technology and Applications >An Exploration of the Power of Max Switch Locations in CNNs
【24h】

An Exploration of the Power of Max Switch Locations in CNNs

机译：CNNS中最大开关位置的力量探索

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, we present the power of max switch locations in convolutional neural networks (CNNs) with two experiments: image reconstruction and classification. First, we realize image reconstruction via a convolutional auto-encoder (CAE) that includes max pooling/unpooling operations in an encoder and decoder, respectively. During decoder operation, we alternate max switch locations extracted from another image, which was chosen from among the real images and noise images. Meanwhile, we set up a classification experiment in a teacher-student manner, allowing the transmission of max switch locations from the teacher network to the student network. During both the training and test phases, we let the student network receive max switch locations from the teacher network, and we observe prediction similarity for both networks while the input to the student network is either randomly shuffled test data or a noise image. Based on the results of both experiments, we conjecture that max switch locations could be another form of distilled knowledge. In a teacher-student scheme, therefore, we present a new max pool method whereby the distilled knowledge improves the performance of the student network in terms of training speed. We plan to implement this method in future work.
机译：在本文中，我们呈现了卷积神经网络（CNNS）中最大开关位置的力量，其中有两个实验：图像重建和分类。首先，我们通过卷积自动编码器（CAE）实现图像重建，其分别包括在编码器和解码器中的MAX池/解凝操作。在解码器操作期间，我们替代从另一个图像中提取的最大开关位置，该位置从真实图像和噪声图像中选择。同时，我们以师生方式设置了分类实验，允许从教师网络传输到学生网络的最大交换机位置。在培训和测试阶段，我们让学生网络从教师网络接收最大开关位置，并且我们观察两个网络的预测相似度，而学生网络的输入是随机洗机的测试数据或噪声图像。基于两个实验的结果，我们猜想最大开关位置可能是另一种形式的蒸馏知识。因此，在教师 - 学生计划中，我们提出了一种新的最大池方法，其中蒸馏知识在训练速度方面提高了学生网络的性能。我们计划在将来的工作中实施这种方法。

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