Digital holographic synthetic aperture method based on the improved SIFT
Why this work is in the frame
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Bibliographic record
Abstract
Digital holographic technology can nondestructively mark the morphology of cells, and also achieve non-contact detection of objects. However, due to the limitation of the numerical aperture of the optical microscope, the spatial bandwidth product of image is lower than the maximum information flux achieved by modern optics, and the imaging resolution is not high. To solve this problem, this paper proposes a synthetic aperture imaging method based on an improved Scale Invariant Feature Transform (SIFT) algorithm. Experiments show that the field of view of the synthetic aperture image is improved by 64.48% compared with that of the sub-aperture image, which effectively expands the measurement range of the sample and can obtain more sample information. The proposed method breaks away from the limits of the area of the detector. Furthermore, the gray variance of the synthetic aperture image also increases which provides a better synthesized three-dimensional image.
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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 | 0.000 | 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