Phase Completion for Fringe Projection Profiler Based on Neural Networks
Why this work is in the frame
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Bibliographic record
Abstract
Fringe projection profiler (FPP) measures the geometry of the target surface by projecting the pre-modulated stripe map onto the surface, and then capture the phase map with a camera. However, the inaccurate exposure or the characteristics of the surface reflectance may influence the imaging quality of the phase map, leaving some over-exposure and under-exposure regions. Addressing to this problem, this paper propose to apply a neural network to complete the phase map. Firstly, we propose a synthetic dataset to simulate the phase map of the inaccurate exposure regions, based on a physical rendering model. After that, we implement a transformer neural network to complete the missing phase information. Experiments show that the proposed neural network can complete the missing information from its neighbouring information, and provide precise completion results.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it