Sports Action Pattern Recognition Method Based on Fuzzy Neural Network Theory

In recent years, with the continuous progress of computer deep learning, neural network and other technologies, a large number of analysis and action recognition have been carried out for various types of motion behaviors through the establishment of relevant models, and the recognition methods of human behavior characteristics characterized by pictures have also been rapidly developed. In this paper, a three-dimensional convolutional neural network with dual resolution is established, and then the motion technology action data set is established through the model, Using the SSD target detection algorithm, the feature vectors extracted from the dual-resolution network are fused and the SVM classification experiment is carried out. The final experimental results show that the algorithm flow designed in this paper is based on the motion recognition of the motion technology action data set established in this paper. On this basis, the recognition results of two resolution neural networks and support vector machines are compared. The effectiveness of this method is verified by the simulation of the constructed sports skill behavior samples.