A Novel Sobel Edge Detection Accelerator Based on Reconfigurable Architecture
Why this work is in the frame
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Bibliographic record
Abstract
A novel Sobel edge detection accelerator based on reconfigurable architecture is proposed to solve the problem of low power-to-performance ratio of traditional Sobel edge detection algorithm in CPU processing. The accelerator adopts pixel level fine grain image data parallel processing and row buffer storage architecture to improve the processing efficiency of edge detection. At the same time, a reconfigurable architecture based on FPGA is built. Through experiments, it can be found that the acceleration effect of the edge detection accelerator on video data is superior to that of the CPU software. Compared with similar accelerators, the acceleration performance of the novel accelerators improves by 10%. The results show that the proposed edge detection accelerator can be used in embedded systems to provide edge detection processing capability with high performance power consumption ratio.
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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 | 0.002 | 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) | 0.002 | 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