Author manuscript, published in "International Symposium on Optomechatronic Technologies, ISOT'10., Toronto: Canada (2010)" Autofocusing-based visual servoing: application to MEMS micromanipulation
Bibliographic record
Abstract
Abstract — In MEMS microassembly areas, different methods of automatic focusing are presented in the literature. All these methods have a common point. Thus, the current autofocusing methods for microscopes need to perform a scanning on all the vertical axis of the microscope in order to find the peak corresponding to the focus (sharpen image). Those methods are time consuming. Therefore, this paper presents an original method of autofocusing based on a velocity control approach which is developed and validated on real experiments. I. OVERVIEW Reliable autofocusing methods are indispensable in the microassembly of hybrid micro-electromechanical systems (MEMS) and for general uses of optical microscopes [6], [8]. Ensuring an optimal focus is essential in industrial vision systems. A good focus ensures sharpen image and thus
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".