mGesture recognition algorithm matlab simulation based on GA-CNN genetic optimization convolutional neural network

Table of Contents 1. Algorithm simulation effect 2. Summary of theoretical knowledge involved in algorithms 2.1 Genetic algorithm optimization stage 2.2 Convolutional neural network classification stage 3.MATLAB core program 4. Obtain the complete algorithm code file 1. Algorithm simulation effect The matlab2022a simulation results are as follows: CNN training results CNN training results after GA […]

[Pytorch] Computer Vision Project – Convolutional Neural Network CNN model recognition image classification

Directory I. Introduction 2. CNN visual interpreter 1. Working principle of convolution layer 3. Detailed step instructions 1. Data set preparation 2.DataLoader 3. Build model CNN 3.1 Set up the device 3.2 Build CNN model 3.3 Set loss and optimizer 3.4 Training and testing loop 4. Model evaluation and result output 1. Preface The overall […]

Image classification recognition and training based on convolutional neural network

1. Introduction Pytorch reproduces the lenet5 model and detects your own handwritten digital images. It is relatively simple to build a model using the torch framework, but you will also encounter many problems. There is a lot of information on the Internet, and the methods of building the model are similar. After I tried to […]

[Power Forecasting] Optimizing the time convolutional neural network DBO-TCN based on the dung beetle algorithm to achieve power load forecasting with matlab code

?About the author: A Matlab simulation developer who loves scientific research. He cultivates his mind and improves his technology simultaneously. For code acquisition, paper reproduction and scientific research simulation cooperation, please send a private message. Personal homepage: Matlab Research Studio Personal credo: Investigate things to gain knowledge. For more complete Matlab code and simulation customization […]

Multiple regression prediction/optimizing the time convolutional neural network DBO-TCN based on the dung beetle algorithm to achieve power load prediction with matlab code

?About the author: A Matlab simulation developer who loves scientific research. He cultivates his mind and improves his technology simultaneously. For code acquisition, paper reproduction and scientific research simulation cooperation, please send a private message. Personal homepage: Matlab Research Studio Personal credo: Investigate things to gain knowledge. For more complete Matlab code and simulation customization […]

CNN-BIGRU classification prediction, based on convolutional neural network-bidirectional gated recurrent unit CNN-BIGRU classification prediction

?About the author: A Matlab simulation developer who loves scientific research. He cultivates his mind and improves his technology simultaneously. For code acquisition, paper reproduction and scientific research simulation cooperation, please send a private message. Personal homepage: Matlab Research Studio Personal credo: Investigate things to gain knowledge. For more complete Matlab code and simulation customization […]

[Wind Power Forecast] Based on convolutional neural network combined with long short memory network CNN-LSTM to realize wind power power multi-input single-output regression prediction with matlab code

?About the author: A Matlab simulation developer who loves scientific research. He cultivates his mind and improves his technology simultaneously. For code acquisition, paper reproduction and scientific research simulation cooperation, please send a private message. Personal homepage: Matlab Research Studio Personal credo: Investigate things to gain knowledge. For more complete Matlab code and simulation customization […]

Convolutional neural network CNN for time series prediction

Article directory 1 Preparation 1.1 Import the library 1.2 Reading data 1.3 Visualization 2 Data preprocessing 2.1 Divide training set and test set 2.2 Divide features and labels 3. Construct a one-dimensional convolutional neural network 4. Training model 4.1 Divide batches 4.2 Set the loss function 4.3 Parameter initialization 4.4 Training model 5 Model results […]