Prioritized Region of Interest Coding in JPEG2000
Why this work is in the frame
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Bibliographic record
Abstract
A method is proposed to encode multiple regions of interest in the JPEG2000 image-coding framework. The algorithm is based on the rearrangement of packets in the code-stream to place the regions of interest before the background coefficients. In order to improve the quality of the reconstructed image, partial background information is included with the regions of interest. The method makes use of a Gaussian priority distribution to assign different priority levels to background and region of interest packets. The priority level is in turn used to determine how much background information should be included with the regions of interest. The proposed technique is fully compatible with the current JPEG2000 standard and allows transmission of different regions of interest with different priorities. Experimental results demonstrating the validity of the proposed approach are presented and compared with existing region of interest coding techniques.
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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 | 0.001 | 0.001 |
| 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