Efficient hardware implementation of an image compressor for wireless capsule endoscopy applications
Why this work is in the frame
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Bibliographic record
Abstract
The paper presents an area- and power-efficient implementation of an image compressor for wireless capsule endoscopy application. The architecture uses a direct mapping to compute the two-dimensional Discrete Cosine Transform which eliminates the need of transpose operation and results in reduced area and low processing time. The algorithm has been modified to comply with the JPEG standard and the corresponding quantization tables have been developed and the architecture is implemented using the CMOS 0.18um technology. The processor costs less than 3.5k cells, runs at a maximum frequency of 150 MHz, and consumes 10 mW of power. The test results of several endoscopic colour images show that higher compression ratio (over 85%) can be achieved with high quality image reconstruction (over 30 dB).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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