Pattern recognition (psychology)

Piecewise linear function

Time delay neural network

Mathematics

Computer science

Piecewise

Sociology

Activation function

Algorithm

Normalization (sociology)

Deep learning

Artificial intelligence

Anthropology

Geometry

Artificial neural network

Mathematical analysis

Convolutional neural network

Convolution (computer science)

Procedia Computer Science

With the continuous development of deep learning, convolution neural network with its excellent recognition performance obtains a series of major breakthrough results in target detection, image recognition and other fields. An improved ReLu segmentation correction Activate function is proposed, by improving the traditional convolution neural network, adding the local response normalization layer, and using the maximum stacking and so on. Based on the Google depth learning platform TensorFlow, the activation function is used to construct the modified convolution neural network structure model, using the CIFAR-10 data set as the neural network input for the model training and evaluation. We analyze effects of different neuron activation function on the neural network convergence speed and the accuracy of image recognition. The experimental results show that using the improved unsaturated nonlinear segment activation function SignReLu, the convergence rate is faster, the gradient vanishing problem is effectively...

Research on convolutional neural network based on improved Relu piecewise activation function