convolutional neural network simple example

1. OverviewConvolution neural network features: On the one hand, the connection between the neurons is non-fully connected, on the other hand, the weights of the connections between some neurons in the same layer are shared (i.e. the same).Left: The image has 1000*1000 pixels, there are 10^6 of hidden layer neurons, to be fully connected, there are 1000*1000*100000=10^12 weight parametersRight: There are al

CNN (convolutional neural Network)Convolutional Neural Networks (CNN) dating back to the the 1960s, Hubel and others through the study of the cat's visual cortex cells show that the brain's access to information from the outside world is stimulated by a multi-layered recepti

that the 2D convolution is actually 3D (the dimensions of the convolution kernel should be kernel_height * kernel_height * input_channel), except that the third dimension is exactly equal to the number of input channels, So the volume after the third dimension on the lost, became a flat two-dimensional feature map, so called 2D convolution.Another way of understanding is that the shape of a convolution core is kernel_height * kernel_height, and there is a input_channel layer, the process of mak

Long time no blog, but also ashamed, recently things more, now time to write a bar Today this article is about neual art, the style transfer algorithm;Article Source:A Neural algorithm of artistic Style, CVPR2015Image Style Transfer Using convolutional neural Networks, CVPR2016 Some time ago there is a fire of the app called Prisma, you can upload a picture of th

the target is detected as the target area ). However, its disadvantage is obvious. First, the size and step length of the sliding window must be set visually. If the sliding window is too small or too large, the target detection accuracy will be reduced if the step length is too large. In addition, CNN network computing is required for each sliding window area. If the sliding window and step length are small, the entire target detection algorithm run

professional students can learn to use this framework, and then perhaps can write a very simple frame of their own, I learn while writing, you look at the side spit groove on the line.The first article in this series is mainly to introduce the great framework from the application level, and some other tutorials, I introduced this kind of application does not need Linux, do not need the GPU (this will be slower, but the first to run up and then consid

The accuracy of the mnist test set is about 90% and 96%, respectively, for single-layer neural networks and multilayer neural networks in the previous two essays. The correct rate has been greatly improved after the multi-layer neural network has been swapped. This time the convolu