黑龙江科技大学学报2025，Vol.35Issue(1)：153-159,7.DOI:10.3969/j.issn.2095-7262.2025.01.023
SLAE-Projected GANs的煤矿井下图像生成方法
Image generation method of coal mine underground based on SLAE-Projected GANs
摘要
Abstract
This paper seeks to address the problem of being unable to obtain high-quality coal mine underground images due to the complex and changing environment,and proposes a coal mine under-ground image generation method based on SLAE-Projected GANs.The study works by adopting the framework of Projected GANs network and injecting noise into the up-sampling structure of the network to ensure the stability of the model in the process of generating images;and introducing the spatial attention module to enhance the model's characterization ability so as to effectively extract the feature information of the image.The results show that PSNR,SSIM and FID of the image generated by this method are 19.065,0.629 and 30.022,respectively,which are better than other existing image generation algo-rithms,and can generate more stable,high-quality and high-resolution images of coal mine underground,which can help the target detection and image recognition of images.关键词
煤矿井下图像/图像生成/空间注意力机制/SLAE-Projected GANsKey words
coal mine underground images/image generation/spatial attention module/SLAE-Pro-jected GANs分类
信息技术与安全科学引用本文复制引用
高志军,孙丽丽,彭重霄,孙银焕..SLAE-Projected GANs的煤矿井下图像生成方法[J].黑龙江科技大学学报,2025,35(1):153-159,7.基金项目
黑龙江省省属高等学校基本科研业务费项目(2024-KYYWF-1082 （）
2022-KYYWF-0565) （）
