Creativity and Sustainable Design of Wickerwork Handicraft Patterns Based on Artificial Intelligence

Protecting and inheriting local traditional handicrafts developing them into characteristic handicraft industries plays a certain role in maintaining social harmony stability. This study proposes an innovative design method for wickerwork patterns to achieve the sustainable development of culture. In order accurately grasp emotional perception law creatively generate pattern schemes accordance with user’s preference, based on deep learning is proposed. Firstly, image recognition model Funan established by using ResNet. The experimental results show that best rate ResNet34 whole dataset 94.36%, modern 95.92%, 93.45%. Secondly, convolution generative adversarial network (DCGAN), scheme generation built. DCGAN can automatically effectively stimulate consumers’ feelings. Finally, designer uses creative pictures as source inspiration, innovates generated images, designs exquisite personality. proposed will increase diversity promote techniques. Moreover, this help companies identify customers’ psychological needs support designers innovatively efficiently creating new cultural innovation solutions.