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Stick to blogging and share your gains in study and work Make a note of yourselfRecord and summarize knowledge points to deepen understandingGive some help to people in need, step less on a pit and take more steps Try to arrange the layout in an appropriate way, with both graphics and text If you write wrong or don't understand, you can lea ...

Practical tutorial | preservation and migration of pytoch model In this article, the author first introduces several typical scenarios of model reuse; Then it introduces how to view the relevant parameter information in the pytoch model; Then it introduces how to load the model, how to carry out additional training and transfer learning of the ...

Author home page( Silicon based workshop of slow fire rock sugar): Slow fire rock sugar (Wang Wenbing) blog silicon based workshop of slow fire rock sugar _csdnblog Website of this article: https://blog.csdn.net/HiWangWenBing/article/details/120600621 catalogue Introduction deep learning model framework Chapter 1 business area analysis on ...

It is very difficult to train deep neural networks, especially in short practice. In this section, we will introduce batch normalization, which is a popular and effective technology to continuously accelerate the convergence speed of deep networks. After the combination, the residual will be introduced quickly, and batch normalization enables r ...

In the actual process of building neural network, forward propagation is easy to realize and has high correctness; The implementation of back propagation is difficult, and there are often bug s. For items requiring high accuracy, gradient test is particularly important. Principle of gradient test The definition of derivative (gradient) in mat ...

preface The image with low resolution caused by enlargement and reduction is converted into an image with high resolution. More attention is paid to filling new pixels in the process of reconstructing the picture. SRCNN is also the ancestor of applying deep learning to image reconstruction. The network structure is very simple, so I deci ...

1, MobileNetV1 network Briefly read Google's 2017 paper mobilenets: efficient revolutionary neural networks for mobile vision applications to experience Depthwise convolution and Pointwise convolution. Also, read the code: https://github.com/OUCTheoryGroup/colab_demo/blob/master/202003_models/MobileNetV1_CIFAR10.ipynb type the code into Colab ...

Transplanting neural network to STM32 A recent project needs to use the network for fitting, and use the fitting results as control. I wonder if I can do neural network calculation directly on the single chip microcomputer, so that I can calculate in real time without relying on the upper computer. Therefore, there are two main problems to be ...

During this period, I participated in the Coggle 30 days of ML punch in and signed up for the CV competition. The competition Title address is: https://challenge.xfyun.cn/topic/info?type=key -points-of-human-face&ch=dw-sq-1 Overview of competition questions: Face recognition is a biometric recognition technology based on human facial f ...

Firstly, a multi-layer perceptron with a single hidden layer is defined, its parameters are initialized by the default method, and a forward operation is performed. import torch from torch import nn from torch.nn import init net=nn.Sequential(nn.Linear(4,3),nn.ReLU(),nn.Linear(3,1)) #Pytoch will be initialized by default print(net) X=torch.r ...