Solder Joints Detection Method Based on Surface Recovery
Why this work is in the frame
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Bibliographic record
Abstract
Machine vision has been widely used in various industrial productions. However, the study for solder joints detection is not enough. This paper presents a solder joints detection method based on surface recovery. For a single gray-scale image, using shape-from-shading (SFS) technology, the surface of the solder joints is recovered. According to the shape distribution, the quality of solder joints is discriminated. In order to improve the accuracy of recovery for real images, hybrid illumination model is introduced and a reflection-component estimation method based on simulated annealing algorithm is designed. Then recovery process of the algorithm is improved. Compared to other detection methods based on two-dimensional images, this method provides more information about explicit physical meaning and make detailed quantitative analysis for solder joints easier. At the same time, even for defect that is difficult to detect, this method also has important research value.
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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 | 0.002 |
| 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