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A Generative Adversarial Network for Infrared and Visible Image Fusion Based on Semantic Segmentation
This paper proposes a new generative adversarial network for infrared and visible image fusion based on semantic segmentation (SSGAN), which can consider not only the low-level features of infrared and visible images, but also the high-level semantic information. Source images can be divided into fo...
Autores principales: | Hou, Jilei, Zhang, Dazhi, Wu, Wei, Ma, Jiayi, Zhou, Huabing |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004063/ https://www.ncbi.nlm.nih.gov/pubmed/33801048 http://dx.doi.org/10.3390/e23030376 |
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