Dev

Ocean Acoustic Tomography — Dev Tier

(5 scenes)

Blind evaluation tier — no ground truth available.

What you get

Measurements (y), ideal forward operator (H), and spec ranges only.

How to use

Apply your pipeline from the Public tier. Use consistency as self-check.

What to submit

Reconstructed signals and corrected spec. Scored server-side.

Parameter Specifications

🔒

True spec hidden — estimate parameters from spec ranges below.

Parameter Spec Range Unit
sound_speed_profile_error -0.48 – 0.72 -
multipath_identification -4.8 – 7.2 -
source/receiver_position -2.4 – 3.6 m
current_velocity_error -0.12 – 0.18 m/s

Dev Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 SwinIR + gradient 0.701 28.6 0.893 0.79 ✓ Certified Liang et al., ICCVW 2021
2 Domain-Adapted-CNN + gradient 0.693 27.84 0.877 0.82 ✓ Certified Domain adaptation CNN
3 ScoreExperimental + gradient 0.668 26.65 0.849 0.81 ✓ Certified Wei et al., 2025
4 DiffusionExperimental + gradient 0.652 25.42 0.815 0.86 ✓ Certified Zhang et al., 2024
5 ExpFormer + gradient 0.632 24.28 0.778 0.89 ✓ Certified Experimental science transformer, 2024
6 PnP-RED + gradient 0.627 24.65 0.791 0.82 ✓ Certified Romano et al., IEEE TIP 2017
7 ResUNet + gradient 0.625 24.42 0.783 0.84 ✓ Certified Residual U-Net baseline
8 Matched Filter + gradient 0.612 23.8 0.761 0.85 ✓ Certified Optimal linear filter
9 Tikhonov + gradient 0.581 22.41 0.707 0.87 ✓ Certified Tikhonov, Doklady 1963
10 PnP-ADMM + gradient 0.570 22.52 0.712 0.8 ✓ Certified ADMM + denoiser prior
11 Wiener Filter + gradient 0.554 21.86 0.684 0.81 ✓ Certified Wiener filtering baseline

Visible Data Fields

y H_ideal spec_ranges

Dataset

Format: HDF5
Scenes: 5

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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