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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...
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| Publicado no: | Entropy (Basel) |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8004063/ https://ncbi.nlm.nih.gov/pubmed/33801048 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e23030376 |
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