Hidden
Acoustic Emission Testing (AE) — Hidden Tier
(5 scenes)Fully blind server-side evaluation — no data download.
What you get
No data downloadable. Algorithm runs server-side on hidden measurements.
How to use
Package algorithm as Docker container / Python script. Submit via link.
What to submit
Containerized algorithm accepting y + H, outputting x_hat + corrected spec.
Parameter Specifications
🔒
True spec hidden — blind evaluation, only ranges available.
| Parameter | Spec Range | Unit |
|---|---|---|
| source_location_error | -0.7 – 2.3 | mm |
| wave_speed_error | 5872.0 – 5992.0 | m/s |
| sensor_coupling_gain | 0.972 – 1.092 | - |
| arrival_time_bias | -0.07 – 0.23 | us |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | DiffusionAE + gradient | 0.618 | 23.87 | 0.764 | 0.87 | ✓ Certified | Song et al., ICLR 2021; SHM application 2024 |
| 2 | SwinIR-AE + gradient | 0.615 | 24.5 | 0.786 | 0.78 | ✓ Certified | Liang et al., ICCV 2021; AE-adapted 2024 |
| 3 | Domain-Adapted ResNet + gradient | 0.531 | 21.23 | 0.656 | 0.78 | ✓ Certified | Tabian et al., Sensors 2019 |
| 4 | PINN-AE + gradient | 0.522 | 21.15 | 0.652 | 0.75 | ✓ Certified | Raissi et al., J. Comput. Phys. 2019; AE extension 2024 |
| 5 | PnP-ADMM + gradient | 0.505 | 19.99 | 0.598 | 0.83 | ✓ Certified | Venkatakrishnan et al., IEEE GlobalSIP 2013 |
| 6 | AE-CNN + gradient | 0.489 | 19.72 | 0.585 | 0.79 | ✓ Certified | Ebrahimkhanlou & Salamone, Struct. Health Monit. 2019 |
| 7 | TDOA-WLS + gradient | 0.430 | 17.4 | 0.47 | 0.84 | ✓ Certified | Kundu, J. Acoust. Soc. Am. 2014 |
| 8 | Sparse TR (L1) + gradient | 0.398 | 16.4 | 0.421 | 0.83 | ✓ Certified | Gao et al., J. Sound Vib. 2016 |
| 9 | Time-Reversal Imaging + gradient | 0.393 | 16.42 | 0.422 | 0.8 | ✓ Certified | Fink, IEEE UFFC 1992; applied to AE: Grosse & Ohtsu 2008 |
Dataset
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%