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Title: The analysis of image recognition for tourism cultural and creative products visual design based on deep learning

Authors: Wei Zhang; Yang Yu; Enhong Liu

Addresses: Jilin Province Research Center for Cultural Tourism Education and Enterprise Development, The Tourism College of Changchun University, Changchun, 130000, China ' School of Artificial Intelligence, The Tourism College of Changchun University, Changchun, 130000, China ' School of Tourism and Culture, The Tourism College of Changchun University, Changchun, 130000, China

Abstract: This work explores consumer demand and preferences for cultural and creative tourism products to enhance the effectiveness of visual design and market competitiveness. A comprehensive model integrating the deep convolutional neural network (DCNN) and deep belief network (DBN) is developed using deep learning technology. This model aims to extract both the underlying features of product images and the semantic features of consumers, thereby providing data support to optimise product design. The results indicate that the constructed model achieves a prediction accuracy of 98.5% and a recall rate of 98.2% in product image recognition, demonstrating its effectiveness in capturing consumer demand characteristics.

Keywords: deep learning; image analysis; product visual design; cultural and creative products; DBN; deep belief network.

DOI: 10.1504/IJDS.2025.151185

International Journal of Data Science, 2025 Vol.10 No.7, pp.114 - 135

Received: 07 Apr 2025
Accepted: 26 Jun 2025
Published online: 16 Jan 2026 *