I will demonstrate how our classification model measures performance. There are subtle differences in deciding how to measure performance. But first, let's create a data frame for 0 and 1.
CNNVery good at classifying out-of-order images, but humans are not. In this article, the authors show why the most advanced deep neural networks still recognize garbled images well, and the reasons for this help reveal that DNN uses an unexpectedly simple strategy to classify natural images.