Time-Frequency Signal Synthesis and Its Application in Multimedia Watermark Detection
Why this work is in the frame
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Bibliographic record
Abstract
We propose a novel approach to detect the watermark message embedded in images under the form of a linear frequency modulated chirp. Localization of several time-frequency distributions (TFDs) is studied for different frequency modulated signals under various noise conditions. Smoothed pseudo-Wigner-Ville distribution (SPWVD) is chosen and applied to detect and recover the corrupted image watermark bits at the receiver. The synthesized watermark message is compared with the referenced one at the transmitter as a detection evaluation scheme. The correlation coefficient between the synthesized and the referenced chirps reaches 0.9 or above for a maximum bit error rate of 15% under intentional and nonintentional attacks. The method provides satisfactory result for detection of image watermark messages modulated as chirp signal and could be a potential tool in multimedia security applications.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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