Research on the Large Model of Tianfu Leisure Sports Culture under Multi-Modal Fusion
          
          
          
          DOI: https://doi.org/10.62381/E254805
           
          Author(s)
          Hongping Wei1,2, Qiang Huang1,2,*, Jinsong Zhang3
          Affiliation(s)
          1Chengdu University of Information Technology, Chengdu, Sichuan, China
2Key Laboratory of Digital Innovation of Tianfu Culture, Sichuan Provincial Department of Culture and Tourism, Chengdu University, Chengdu, Sichuan, China
3Ziyang Yanjiang District Happy Bowen School, Ziyang, Sichuan, China
*Corresponding Author
          Abstract
          This study focuses on the innovative application of multi-modal fusion technology in the field of Tianfu leisure sports culture, aiming to construct a comprehensive, accurate and intelligent large model of Tianfu leisure sports culture. Against the backdrop of the in-depth advancement of the national cultural digitalization strategy and the full implementation of the national fitness strategy, by integrating multi-source data such as text, images, audio, and video, and applying advanced deep learning algorithms, it aims to deeply mine and understand the rich connotations and diverse characteristics of Tianfu leisure sports culture. The study systematically expounds the principles of multi-modal fusion technology, data acquisition and preprocessing methods, model construction and training strategies, and empirically evaluates the application effects of the model in actual scenarios such as leisure sports project recommendation, cultural dissemination, and event organization. The results show that this large model can effectively enhance the digital presentation level of Tianfu leisure sports culture, optimize user experience, empower the development of the leisure sports industry, and provide new ideas and methodological support for the inheritance and innovation of regional leisure sports culture.
          Keywords
          Multi-Modal Fusion; Tianfu Leisure Sports Culture; Large Model; Cultural Digitalization
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