论文标题
分类器的自动编码器看门狗离群值检测
Autoencoder Watchdog Outlier Detection for Classifiers
论文作者
论文摘要
神经网络经常被描述为黑匣子。经过培训的通用神经网络，可以区分小猫和小狗，将kumquat的图片归类为小猫或小狗。 AutoCoder Watch Dog Screens经过训练的分类器/回归机器在处理之前输入候选者，例如首先测试神经网络输入是小狗还是小猫。使用MNIST图像使用卷积神经网络和卷积自动编码器看门狗提出了初步结果。
Neural networks have often been described as black boxes. A generic neural network trained to differentiate between kittens and puppies will classify a picture of a kumquat as a kitten or a puppy. An autoencoder watch dog screens trained classifier/regression machine input candidates before processing, e.g. to first test whether the neural network input is a puppy or a kitten. Preliminary results are presented using convolutional neural networks and convolutional autoencoder watchdogs using MNIST images.
