A Quad-Sampling Wide-Dynamic-Range Pulse-Frequency Modulation Pixel
Bibliographic record
Abstract
We present a wide dynamic range (WDR) CMOS image sensor structure using the pulse-frequency modulation (PFM) pixel. The proposed pixel achieves a dynamic range (DR) of 124 dB with 8-bit resolution and operates in 60 frames/s. A quad-sampling technique is implemented that successfully reduces the pixel size by only using a 6-bit counter within the pixel. The sampling method incorporates cooperation between the pixel and column circuits to generate an automatically compressed signal that can be directly displayed without post-processing. This design has been verified through the field-programmable gate array (FPGA) implementation with a sample pixel. According to the experimental results, the sensor signal-to-noise ratio (SNR) is mainly limited by the quantization noise of the light-to-frequency conversion. The maximum SNR is 48 dB, and the common SNR dip is successfully avoided. In addition, the achievable array size is determined by all sampling periods and can be of megapixels with appropriate designs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".