Low power design of Motion Compensation module for MPEG-4 video transcoder in DCT domain
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we propose optimization techniques to achieve low power design for a transcoder's Motion Compensation module for an MPEG-4 compressed video stream, in the DCT domain on both the algorithmic and implementation level. At the algorithmic level, the low power design is achieved by employing the 3-2-1 partial information scheme coupled with the reduction of the bit precision for the constant transform matrix to two bits after the binary point. The simulation results show that the reduction of bit precision virtually induces no loss in PSNR measure except in the most significant digits of the DCT-CMs constants. At the implementation level optimization the proposed design outperforms the conventional scheme by having 12.26%, 9.9% and 12.13% reduction in power, time, and area respectively.
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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 | 0.000 | 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