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This paper presents a comprehensive framework for classifying spatial features in museum displays using artificial intelligence deep learning technology. It includes the construction of a benchmark dataset for training spatial instance CNN classifier images, which significantly enhances the efficiency of data analysis and improves the design elements' quantitative analysis potential for museum exhibition spaces. This framework will greatly assist in the early selection of spatial structure and design elements intention in museums.

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Research on the Design Auxiliary System of Museum Exhibition Space Based on Artificial Intelligence

  • 会议论文

  • 发表日期：

    2025年

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  • Fang Zhang,
  • Zhenlun Sun

摘要

This paper presents a comprehensive framework for classifying spatial features in museum displays using artificial intelligence deep learning technology. It includes the construction of a benchmark dataset for training spatial instance CNN classifier images, which significantly enhances the efficiency of data analysis and improves the design elements' quantitative analysis potential for museum exhibition spaces. This framework will greatly assist in the early selection of spatial structure and design elements intention in museums.