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Journal: Sensors (Basel, Switzerland)
Article Title: Adversarial Networks for Scale Feature-Attention Spectral Image Reconstruction from a Single RGB
doi: 10.3390/s20082426
Figure Lengend Snippet: Visual comparison of the hyperspectral recovery of four selected images at 570 nm from the ICVL dataset . From top to bottom: sparse coding , SCAUNet-GAN , SAPUNet-GAN, SAPWNet-GAN, and ground-truth.
Article Snippet: The database images were acquired using a
Techniques: Comparison
Journal: Sensors (Basel, Switzerland)
Article Title: Adversarial Networks for Scale Feature-Attention Spectral Image Reconstruction from a Single RGB
doi: 10.3390/s20082426
Figure Lengend Snippet: Quantitative evaluation on the Chakrabarti dataset in comparison with several state-of-the-art hyperspectral reconstructing methods: Yan et al. , Arad et al. , Nguyen et al. , Kawakami et al. .
Article Snippet: The database images were acquired using a
Techniques: Comparison
Journal: Sensors (Basel, Switzerland)
Article Title: Adversarial Networks for Scale Feature-Attention Spectral Image Reconstruction from a Single RGB
doi: 10.3390/s20082426
Figure Lengend Snippet: Detailed analysis of the proposed SAPWNet with different settings. HSGAN, hyperspectral reconstruction GAN with U-Net generator; FP, feature pyramid without scale attention; SAM, scale attention module; W-Net, using W-Net replacing the U-Net.
Article Snippet: The database images were acquired using a
Techniques: