Hidden

Eddy Current Imaging — Hidden Tier

(3 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
liftoff_distance -0.14 – 0.46 mm
conductivity_error 57.58 – 59.38 MS/m
excitation_frequency_drift 99.3 – 102.3 kHz
probe_tilt -0.28 – 0.92 deg

Hidden Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 DiffEC + gradient 0.731 30.28 0.921 0.8 ✓ Certified Gao et al., NeurIPS 2024
2 PhysEC + gradient 0.711 28.62 0.893 0.84 ✓ Certified Chen et al., IEEE Trans. Magn. 2024
3 SwinEC + gradient 0.707 28.45 0.89 0.83 ✓ Certified Wang et al., NDT&E Int. 2023
4 ECNN-Defect + gradient 0.624 24.03 0.77 0.88 ✓ Certified Zhang et al., NDT&E Int. 2021
5 TransEC + gradient 0.623 24.15 0.774 0.86 ✓ Certified Li et al., IEEE Trans. Ind. Electron. 2022
6 MUSIC-EC + gradient 0.612 24.03 0.77 0.82 ✓ Certified Skarlatos et al., NDT&E Int. 2012
7 DnCNN-EC + gradient 0.509 20.33 0.614 0.8 ✓ Certified Gao et al., IEEE Sens. J. 2019
8 EC-Deconv + gradient 0.382 16.44 0.423 0.74 ✓ Certified Bowler, J. Appl. Phys. 1994
9 TV-EC + gradient 0.304 12.96 0.267 0.84 ✓ Certified Sabbagh et al., IEEE Trans. Magn. 2010

Dataset

Scenes: 3

Scoring Formula

0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)

PSNR: 40% SSIM: 40% Consistency: 20%
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