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Record W2067795404 · doi:10.1109/ted.2012.2231961

A Quad-Sampling Wide-Dynamic-Range Pulse-Frequency Modulation Pixel

2012· article· en· W2067795404 on OpenAlex
Tsung-Hsun Tsai, Richard Hornsey

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2012
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsYork University
FundersCMC Microsystems
KeywordsPixelDynamic rangeSampling (signal processing)Quantization (signal processing)Wide dynamic rangeElectronic engineeringImage resolutionHigh dynamic rangeImage sensorComputer scienceModulation (music)EngineeringPhysicsAlgorithmComputer visionAcoustics

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.247
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it