One-shot color mapping of a ray direction field for obtaining three-dimensional profiles integrating deep neural networks
Why this work is in the frame
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Bibliographic record
Abstract
A method for simultaneously and instantly obtaining both a three-dimensional (3D) surface and its inclination angle distribution from a single image captured by an imaging system equipped with a coaxial multicolor filter that integrates deep neural networks (DNNs) is proposed. The imaging system can obtain a light-ray direction in the field of view through one-shot color mapping. Light rays reflected from a 3D surface, even if it has microscale height variations with a small inclination angle distribution, can be assigned different colors depending on their directions by the imaging system. This enables the acquisition of the surface inclination angle distribution. Assuming a smooth and continuous 3D surface, it is possible to reconstruct the surface from a single captured image using DNNs. The DNNs can provide the height variations of the 3D surface by solving a nonlinear partial differential equation that represents the relationship between height variation and the direction of light rays. This method is validated analytically and experimentally using microscale convex surfaces.
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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