Abstract
Designing the appearance of clothing can effectively enhance its attractiveness and expand its marketability. This paper briefly introduces the Convolutional Neural Network (CNN) and applies it to the recognition and evaluation of clothing pattern styles to assist in evaluating clothing appearance design. A case analysis was then conducted. Firstly, the CNN algorithm was compared with the traditional Back-Propagation Neural Network (BPNN) algorithm, and then the design scheme proposed in this paper, called "Sanduo and Jiuru", was evaluated. The results showed that, compared to the BPNN algorithm, the CNN algorithm not only converged faster during training but also demonstrated superiority after the convergence became stable. In addition, the test set also verified the accuracy of the CNN algorithm in recognizing and evaluating clothing pattern styles. The evaluation of the "Sanduo and Jiuru" design was also very similar to human evaluation, and its excellence was analyzed accordingly.
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