Optical Correlation Detection and Identification of Low Contrast Targets Under Cluttered Background
Why this work is in the frame
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Bibliographic record
Abstract
Optical images detection,automatic identification,real-time tracking and precise positioning can be realized with hybrid optoelectronic joint transform correlator.However,when the practical target images have low contrasts and large background noises,the correlation peak contrast would be significantly reduced,even non correlation peaks appear.In this paper,the histogram equalization method combined with a low-pass filter in the spatial frequency domain was adopted.With this method,the image contrast is greatly improved,the background noises are reduced,and a sharp correlation peaks are obtained.The recognition problems of low-contrast target images under cluttered background are solved.Large amounts of computer simulations and optical experiments show that,compared to other complicated algorithms,this method owns simple algorithm,fast processing and good result.
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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