Programmer Think

1, Introduction of BP neural network traffic sign recognition Road traffic signs are used to prohibit, warn, instruct and restrict road users to use roads in an orderly manner to ensure travel safety If the road traffic signs can be recognized automatically, the occurrence of road traffic accidents will be greatly reduced However, due to the c ...

I wrote the last blog in 2021 and the first blog in 2022 at 23:04 on December 31, 2021. This year's motto: if there is a heat and a light, it will make a firefly. You can also make a light in the dark. You don't have to wait for the torch. After that, if there is no torch, I will be the only light. Introduction A few days ago, I ...

catalogue 1, Network principle II. Algorithm steps 3, Code implementation (Java) 4, jar package used 1, Network principle Hopfield neural network (HNN) is a fully interconnected feedback neural network, in which each neuron is connected with other neurons. Hopfield neural network is mainly divided into discrete Hopfield neural network ( ...

Programmer's view of love: love is a dead cycle, once executed, it will fall into; Falling in love with someone is a memory leak - you can never release it; When you really love someone, that is constant limit, which will never change; Girlfriend is a private variable, which can only be called by my class; Lover is a pointer. You must pay atten ...

In the first two articles, we have introduced the autoregressive model pixelcnn and how to deal with multidimensional input data. In this article, we will focus on one of the biggest limitations of pixelcnn (i.e. blind spots) and how to improve it to repair it.In the first two articles, we introduced the concept of generating model PixelCNN and ...

Recently, when writing a paper, I encountered the problem of feature graph visualization, so I sorted the methods to solve this problem into notes. 1: Why visualization? It is often said that the essence of CNN is to extract features, but we don't know what features it extracts, which regions really play a role in recognition, or what the net ...

Like RNN neurons, LSTM neurons can maintain memory in their pipeline to allow solving sequence and time problems without disappearing gradient problems affecting their performance. Using the ancient poetry data set, the LSTM neural network model is used to train and automatically generate Chinese Tibetan head poetry. import pandas as pd i ...

I CGAN and ACGAN 1. CGAN The input of ordinary GAN is an N-dimensional normal distribution along with machine number \color{red} random number Random number, and CGAN wi ...

Pytorch autoencoder (self coding, unsupervised learning) 1, Compression and decompression There is a neural network. What it is doing is receiving a picture, then coding it, and finally restoring it from the coded picture Assuming that the neural network is like this, corresponding to the picture just above, we can see that the picture is ...

Convolutional neural network series preface In this article, we use a custom implemented LeNet-5 neural network architecture to perform image classification on MNIST data sets. 1, Integration LeNet was founded in 1998 by Yann Lecun, Leon bottom, yoshua bengio, and Patrick Haffner My thesis Gradient-Based Learning Applied To ...