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Record W2013639962 · doi:10.1145/1284480.1284502

A multisampling time-domain CMOS imager with synchronous readout circuit

2007· article· en· W2013639962 on OpenAlexaff
Fernando de Souza Campos, Ognian Marinov, Naser Faramarzpour, Fayçal Saffih, M. Jamal Deen, Jacobus W. Swart

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComparatorFixed-pattern noisePixelCMOSFrame rateComputer sciencePhotodiodeDynamic rangeOffset (computer science)Frame (networking)Read-write memoryTransistorImage sensorElectronic engineeringComputer hardwareVoltageElectrical engineeringPhysicsEngineeringOptoelectronicsArtificial intelligenceTelecommunicationsComputer vision

Abstract

fetched live from OpenAlex

A novel multisampling time-domain architecture for CMOS imagers with synchronous readout and wide dynamic range is proposed. The architecture was implemented in a prototype of imager with 32x32 pixel array fabricated in AMS CMOS 0.35µm and was characterized for sensitivity and color response. The pixel is composed of an n+/psub photodiode, a comparator and a D flip-flop having 16% fill-factor and 30µmx26µm dimensions. The multisampling architecture requires only a 1 bit per pixel memory instead of 8 bits which is typical for time-domain active pixel architectures. The advantage is that the number of transistors in the pixel is low, saving area and providing higher fill-factor. The maximum frame rate is analyzed as a function of number of bits and array size. The analysis shows that it is possible to achieve high frame rates and operation in video mode with 10 bits. Also, we present analysis for the impact of comparator offset voltage in the fixed pattern noise.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.765

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.005
GPT teacher head0.193
Teacher spread0.187 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2007
Admission routes1
Has abstractyes

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