FGL-GAN: Global-Local Mask Generative Adversarial Network for Flame Image Composition

It is important to reduce the danger of collecting flame image data sets by compositing flame images by computer. In this paper, a Global-Local mask Generative Adversarial Network (FGL-GAN) is proposed to address the current status of low quality composite flame images. First, FGL-GAN adopts a hiera...

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Detalles Bibliográficos
Autores principales: Qin, Kui, Hou, Xinguo, Yan, Zhengjun, Zhou, Feng, Bu, Leping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460294/
https://www.ncbi.nlm.nih.gov/pubmed/36080788
http://dx.doi.org/10.3390/s22176332

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460294/
https://www.ncbi.nlm.nih.gov/pubmed/36080788
http://dx.doi.org/10.3390/s22176332

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