Tag：neural network
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Time：2021-6-12
By Rashida nasrin suckyCompile VKSource: medium Neural networks have been developed to simulate the human brain. Although we haven’t done that yet, neural network is very effective in machine learning. It was very popular in the 1980s and 1990s and has become more and more popular recently. The computer is fast enough to run a […]
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Time：2021-6-11
Today, I’d like to introduce five papers on ECCV 2020 oral. ECCV, CVPR and iccv are called the top three conferences in the field of computer vision. A total of 5025 articles were submitted to ECCV 2020, of which 1361 were accepted, with an acceptance rate of 27%. ECCV 2020 accepted papers list address: https://eccv2020.eu/accepted-papers/ […]
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Time：2021-6-6
By pulkit SharmaCompile FlinSource: analyticsvidhya introduce Image classification is one of the most important applications of computer vision. Its applications range from object classification from autopilot to recognition of blood cells in medical industry, from identifying defective items in manufacturing industry to establishing systems that can classify people wearing masks or not. In all of […]
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Time：2021-6-6
preface During the Chinese new year, I had nothing to do with my own blog. I happened to see an article I had written before An article to solve the machine learning, deep learning entry doubts This article was originally published in mid-2018, which would be exactly the sameDeep learning and neural network without brainWhen […]
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Time：2021-6-3
Seven new tutorials have been added: Pytorch official Chinese course 1.7 Learn pytorch Pytorch deep learning: a 60 minute shock tensor torch.autogradA brief introduction to neural network Training classifier Learn pytorch through examples Warm up: numpy Pytorch: tensor Pytorch: tensor and autograd Pytorch: define a new autograd function PyTorch：nn PyTorch：optim Pytorch: Customnnmodular Pytorch: control flow […]
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Time：2021-6-3
“Do it yourself neural network” is an e-book, which is the first and only one neural network book using Java. What “do it yourself neural network” teaches you is:Understand the principle of neural network and various design methods, simple grounding gas is not boring;Understand the realization of each component of neural network in the program, […]
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Time：2021-6-1
This article is a very interesting project I saw last year. I tried to imitate its code and write a similar project, but it has not been completed. Here is a related blog translated by the original author. Maybe more people are interested in it. Project demonstration: demo implemented by the original author with JavaScript […]
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Time：2021-5-30
1、 Threshold logic unit Threshold logic unit (Tlu), which can input a group of weighted coefficient quantity, sum them, if the sum reaches or exceeds a certain threshold, output a quantity. For example, the inputs are A1, A2,…, an and the weights W1, W2, …, wn。 Then there is the sum of AI x wi […]
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Time：2021-5-29
Neural network is very cute! 0. ClassificationThe most important use of neural network is classification. In order to give you an intuitive understanding of classification, let’s take a look at a few examplesSpam identification: now there is an e-mail that extracts all the words that appear in it and sends them to a machine. The […]
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Time：2021-5-8
1. The simplest schematic diagram of neural network It is divided into input layer, output layer and hidden layerFor such a simplest neural network, there is only one hidden layerIn the graph, the line represents the neuron, which is obtained by a certain operation from the node of the upper layer. That is to say, […]
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Time：2021-5-8
Classification network import torch import torch.nn.functional as F from torch.autograd import Variable import matplotlib.pyplot as plt #Construction data n_data = torch.ones(100, 2) x0 = torch.normal(3*n_data, 1) x1 = torch.normal(-3*n_data, 1) #The tags are Y0 = 0 and Y1 = 1 y0 = torch.zeros(100) y1 = torch.ones(100) #Connect data through. Cat x = torch.cat((x0, x1), 0).type(torch.FloatTensor) […]
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Time：2021-4-30
In this paper, we will study a convolutional neural network to solve the coin recognition problem, and we will implement a convolutional neural network in keras.net. Here, we will introduce convolutional neural network (CNN) and propose a CNN architecture, which we will train to recognize coins. What is CNN? As we mentioned in the previous […]
