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Table 3 Effects on attention-aware layer (AAL)

From: Sparse self-attention aggregation networks for neural sequence slice interpolation

Synthesis

cremi_triplet A

cremi_triplet B

cremi_triplet C

mouse_triplet

 

PSNR

SSIM

PSNR

SSIM

PSNR

SSIM

IE

PSNR

SSIM

IE

KEL [9]

17.59

0.4354

15.88

0.3415

16.08

0.3506

30.82

13.46

0.1867

42.62

SSA [30]

18.12

0.4292

16.41

0.3425

16.33

0.3357

28.91

14.86

0.2261

35.41

AAL(Ours)

18.26

0.4374

16.79

0.3712

16.46

0.3575

28.38

15.04

0.2156

34.81

  1. Compared with kernel estimation layer (KEL) and interlaced sparse self-attention layer (SSA), the proposed attention-aware layer (AAL) presents a significant improvement on both the cremi_triplet and mouse_triplet datasets. Lower IEs indicates better performance
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BioData Mining

ISSN: 1756-0381