Adaptive Multiple-Resolution CMOS Active Pixel Sensor
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
A smart image sensor with adaptive multiple resolution ability is presented. This sensor is based on the quadtree decomposition algorithm, which decomposes an image into square homogeneous regions. After the image is segmented, only the value of the block and its size are stored or transmitted. On-chip implementation can solve the information bottleneck problem by reducing the amount of data for transmission. Good compression results can be achieved for scenes with predominant and homogeneous backgrounds. The algorithm is implemented on chip in a mixed-signal column parallel architecture in 0.35-mum 4M2P n-well TSMC CMOS technology available through MOSIS. Typical power dissipation for the test chip with 32times32 pixels is 70 mW at VDD=3.3 V
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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 | 0.000 | 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