Cost Effective Reconfigurable Architecture for Stream Processing Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>This paper presents an approach for development of costeffective custom video / image processing systems. The approach utilizes the concept of temporal partitioning of resources in the partially reconfigurable FPGA devices. Paper proposes architecture of the multi-mode video-stream processor with cyclically reconfigurable structure. The cost-effectiveness of the proposed approach has been analyzed on the basis of experiments conducted on Multi-mode Adaptive Reconfigurable System (MARS) platform that was developed for that purpose. The video-processing cores associated with stereo-vision algorithms have been developed, tested and analyzed. The experiments have shown that the cost-effectiveness of the systems based on proposed approach can be better than the traditional approaches based on large statically configured FPGAs. </p>
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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 | 0.002 | 0.001 |
| 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