基于ACGAN的火灾图像生成

Yang Zhikai, Bu Leping, Wang Teng, Zheng Tianrui, Wu Fen
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引用次数: 6

摘要

为了解决CNN训练中火灾图像数据难以获取的问题,本文讨论了利用生成式对抗网络生成火灾图像的方法。讨论了如何根据已知的观测变量生成理想的火灾图像。根据信息GAN和ACGAN的结构,提出了一种用于火灾图像生成的GAN结构。选取火灾区域作为已知的观测变量,生成相应的火灾图像。实验表明,该网络结构可以根据观测变量的值生成所需的图像。生成图像的质量与观测变量在数据集中的分布有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fire Image Generation Based on ACGAN
In order to solve the problem that it is difficult to obtain fire image data in CNN training, this paper discusses the method of generating fire image by means of generative adversarial networks. How to generate the desired fire image according to the known observation variables is discussed. According to the structure of InfoGAN and ACGAN, a GAN structure for generating fire image is proposed. Fire area is selected as a known observation variable to generate the corresponding fire image. Experiments show that the network structure can generate the required images according to the values of a observed variables. And the quality of the generated image is related to the distribution of observed variables in the data set.
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