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可定制的图案合成:用于灯设计的深度生成方法.

Mengran Yan1,2, Chun Tang1, Jida Yan3

  • 1Fine Arts Department, Bozhou University, Bozhou City, Anhui Province, China.

PeerJ. Computer science
|March 26, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种AI生成模型,用于可定制的灯图案,将传统美学与现代设计融合在一起. 这种新的方法显著优于现有方法,在人工智能驱动的模式创建中保持文化真实性.

关键词:
深度学习是一种深度学习.生成型模型是一种生成型模型.灯模式的灯模式.模式合成模式的合成.

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科学领域:

  • 计算机视觉 计算机视觉
  • 人工智能的人工智能
  • 保护文化遗产 保护文化遗产

背景情况:

  • 图案设计对于传统灯生产至关重要,嵌入文化和艺术意义.
  • 现有的模式生成方法可能缺乏灵活性和将传统美学与现代设计相结合的能力.
  • 生成模型提供了创造新和可定制模式的潜力.

研究的目的:

  • 为可定制的灯图案开发一个创新的生成模型.
  • 使用生成对抗网络 (GAN) 将古典美学与现代设计特征集成.
  • 为了提高设计灵活性,同时在模式创作中保持文化真实性.

主要方法:

  • 开发了一个基于生成对抗网络 (GAN) 的模式生成框架.
  • 在十个类别的17000多个图案图像的广泛数据集上训练模型.
  • 采用噪声载体混合化和后处理技术,以提高控制和灵活性.

主要成果:

  • 获得了5.259的高初始得分,优于其他基于GAN的方法.
  • 证明了传统模式元素与人工智能驱动设计的有效整合.
  • 该模型提供了增强的设计灵活性和对图案生产的精确控制.

结论:

  • 开发的基于GAN的模型成功生成可定制的灯图案.
  • 这种方法有效地将传统的艺术价值观与现代人工智能能力结合在一起.
  • 这种工具为现代化灯设计提供了巨大的潜力,同时保护文化遗产.