Bibliographic record
Abstract
This thesis deals with the designing of CMOS image sensors with in-pixel analog-to-digital conversion. A 2-stage memory write scheme for Pulse-Width-Modulation digital pixel sensors is proposed. It utilizes the characteristics of Gray-code counters and partitions a single data write operation into two separated write operations such that the size of the in-pixel memory can be significantly reduced. A Pulse-Frequency-Modulation pixel significantly reduces the integration time without sacrificing the dynamic range. Finally, a Pulse-Frequency-Modulation Digital Pixel Sensor with an in-pixel variable reference voltage is proposed. As compared with conventional Pulse-Frequency-Modulation pixels, the proposed architecture improves the dynamic range by adaptively adjusting the reference voltage in the pixel. All proposed digital pixel sensors are designed in TSMC-0.18μm 6-Metal 1-Poly 1.8 V CMOS technology and analyzed using Spectre from Cadence Design Systems with BSIM3V3 device models. The effectiveness of the proposed digital pixel sensors is validated using simultation.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".