An Innovative Approach to Skill Transmission and Education of Traditional Folk Crafts Empowered by Neural Network Algorithms

As an important part of traditional Chinese culture, the integration of traditional folk handicrafts into the educational curriculum is conducive to innovative curriculum planning in conjunction with the educational goals of the new era. In this paper, based on the protection and inheritance of handicraft culture, we design a help program for handicraft design. Using ultra-high resolution technology, the image is enhanced and restored to realize the reconstruction of the image. Construct the cubic basis function and combine the double cubic interpolation method to preprocess the image. A DLSS neural network model is built and a temporal dimension is added to the spatial sampling to increase the range of sampling number. An autoencoder recognition function is utilized to capture the spatial and temporal variations of the features. Consumers are taken as the core to establish an innovative teaching model to help the inheritance and innovation of traditional folk handicrafts. In the group cognitive law, the subjects' cognitive bias increases from 0.1264 to 2.2998, and the cognitive rate gradually decreases from 1.4284 to 0.5966, which show the opposite trend of change, and every effort should be made to avoid the design being too abstract in the process of dissemination of folk traditional handicrafts inheritance. In terms of dissemination willingness, 63.425% of the audience is willing to disseminate folk traditional handicraft culture, and the dissemination willingness is strong.