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Abstract：
This article describes constructing an embedded system for a painting art and style presentation platform, achieving the automatic integration of digital painting art with traditional art design. The frontend components are designed using the Bootstrap framework, with Django as the web development framework and TensorFlow architecture integrated into the code. Furthermore, the Inception module and residual connections are introduced to optimize the visual geometry group (VGG) network for recognizing and analyzing image texture features. Compared to other models, experimental results indicate that the proposed model demonstrates a 2.6% increase in image style classification accuracy, reaching 87.34% and 95.33% in architectural and landscape image classification, respectively. The system\'s operational outcomes reveal that the proposed platform alleviates the burden on the logical function modules of the system, enhances scalability, and promotes the automated fusion of digital painting art with traditional art design expression.
摘要：
本文描述了构建一个用于绘画艺术和风格呈现平台的嵌入式系统，实现数字绘画艺术与传统艺术设计的自动融合。前端组件使用Bootstrap框架设计，以Django为Web开发框架，将TensorFlow架构集成到代码中。此外，引入了Inception模块和残差连接，以优化视觉几何组（VGG）网络，用于识别和分析图像纹理特征。与其他型号相比，实验结果表明，该模型在图像风格分类精度上提高了2.6%，建筑和景观形象分类达到87.34%和95.33%，分别。系统的运行结果表明，所提出的平台减轻了系统逻辑功能模块的负担，增强可扩展性，促进数字绘画艺术与传统艺术设计表达的自动化融合。
