Convolutional Neural Network in Computer Aided Ceramic Art Design

Abstract

On the basis of practicality, ceramic art design constantly increases its aesthetic artistry, bringing renewal and enjoyment to human life. Ceramic art is a complex art form, and the aesthetic feeling of its works is highlighted. It is need to fully collect the technology and innovative design ideas of skilled craftsmen. Only by fully exerting the utility function and spiritual function of the products themselves can the design beauty be highlighted. In this paper, taking ceramic art design as the breakthrough point, the characteristics and influencing factors of its design beauty are analyzed, a three-dimensional modeling algorithm of ceramic art products based on convolutional neural network (CNN) is proposed, and the computer-aided ceramic art design strategy under the influence of artificial intelligence is explored. Compared with the traditional support vector machine (SVM) algorithm, the algorithm in this paper improves the accuracy of ceramic art image recognition by 28.64% and the recall by 19.68%, and the digital image processing effect of SVM algorithm takes longer. The computer-aided design (CAD) method of ceramic image based on deep learning (DL) proposed in this paper can effectively solve the problem of unclear image and insufficient stereo, and at the same time keep the definition of ceramic image, and can accurately locate the edge contour of ceramic artwork.