Chinese gesture language recognition method based on convolutional neural network
A convolutional neural network and recognition method technology, applied in biological neural network models, neural architecture, character and pattern recognition, etc., can solve the problems of expensive wearable devices and inconvenient use.
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[0013] The network structure of convolutional neural network is mainly composed of convolutional layer, pooling layer and fully connected layer. The convolutional layer is also a feature extraction layer. It extracts different features of the image by using different convolution kernels to perform convolution operations on the input image. The convolution operation makes the parameters of the convolution kernels shared in different positions of the image, which can greatly reduce the model The parameters of , reducing the training time, and the extracted features have nothing to do with the spatial position, the expression is as follows:
[0014]
[0015] in, It is the jth neuron of the L layer; f( ) represents the nonlinear activation function function, which has many common functions, such as Sigmoid function, hyperbolic tangent function (tanh), linear correction unit (ReLU), etc.; W Is the convolution kernel; * represents the convolution operation; b is the weight.
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