Public
Atomic Force Microscopy (AFM) — Public Tier
(3 scenes)Full-access development tier with all data visible.
What you get
Measurements (y), ideal forward operator (H), spec ranges, ground truth (x_true), and true mismatch spec.
How to use
Load HDF5 → compare reconstruction vs x_true → check consistency → iterate.
What to submit
Reconstructed signals (x_hat) and corrected spec as HDF5.
Parameter Specifications
✓
True spec visible — use these exact values for Scenario III oracle reconstruction.
| Parameter | Spec Range | True Value | Unit |
|---|---|---|---|
| tip_shape_convolution | -0.15 – 0.15 | 0.0 | - |
| piezo_nonlinearity | -1.0 – 2.0 | 0.5 | - |
| thermal_drift | -0.2 – 0.4 | 0.1 | nm/s |
| scanner_hysteresis | -2.0 – 4.0 | 1.0 | - |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
9.82 dB
SSIM 0.5129
Scenario II (Mismatch)
8.93 dB
SSIM 0.1796
Scenario III (Oracle)
18.82 dB
SSIM 0.1493
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 9.37 | 0.5121 | 9.18 | 0.1725 | 18.71 | 0.1455 |
| scene_01 | 10.22 | 0.5099 | 8.31 | 0.1922 | 18.93 | 0.1489 |
| scene_02 | 10.19 | 0.5135 | 8.93 | 0.1841 | 18.88 | 0.1581 |
| scene_03 | 9.49 | 0.5161 | 9.31 | 0.1697 | 18.75 | 0.1448 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | SPM-Former + gradient | 0.780 | 31.79 | 0.94 | 0.93 | ✓ Certified | Chen et al., Nano Letters 24:3891, 2024 |
| 2 | DiffusionAFM + gradient | 0.776 | 32.05 | 0.943 | 0.89 | ✓ Certified | Score-based diffusion for SPM image restoration, 2024 |
| 3 | DeepAFM + gradient | 0.733 | 28.95 | 0.899 | 0.92 | ✓ Certified | Somnath et al., NPJ Comput. Mater. 2021 |
| 4 | Self-Sup AFM + gradient | 0.726 | 28.79 | 0.896 | 0.9 | ✓ Certified | Self-supervised tip artifact deconvolution, 2023 |
| 5 | PnP-ADMM + gradient | 0.629 | 24.24 | 0.777 | 0.88 | ✓ Certified | Venkatakrishnan et al., IEEE GlobalSIP 2013 |
| 6 | Wiener Deconv + gradient | 0.576 | 21.84 | 0.683 | 0.92 | ✓ Certified | Klapetek et al., Meas. Sci. Technol. 2011 |
| 7 | Plane Fit + gradient | 0.450 | 17.8 | 0.49 | 0.88 | ✓ Certified | Nečas & Klapetek, Open Physics 2012 |
Visible Data Fields
y
H_ideal
spec_ranges
x_true
true_spec
Dataset
Format: HDF5
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%