MétaCan
Menu
Back to cohort
Record W4236518274 · doi:10.32920/ryerson.14645022

A CMOS voltage-mode image sensing system

2021· preprint· en· W4236518274 on OpenAlexaff
Junlong Zhang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCMOSImage sensorElectronic engineeringPixelCMOS sensorCorrelated double samplingElectronic circuitSIGNAL (programming language)Noise (video)Electrical engineeringComputer scienceVoltageEngineeringImage (mathematics)Artificial intelligenceAmplifier

Abstract

fetched live from OpenAlex

A CMOS image sensor consists of a light sensing region that converts photonic energy to an electrical signal and a peripheral circuitry that performs signal conditioning and post-processing. This project investgates the principle and design of CMOS active image sensors. The basic concepts and principle of CMOS image sensors are investigated. The advantages of CMOS image sensors over charge-coupled device (CCD) image sensors are presented. Both passive pixel sensors (PPS) and acive pixel sensors (APS) are examined in detail. The noise of CMOS image sensors is investigated and correlated double sampling (CDS) techniques are examined. The design of APS arrays, CDS circuits and 8-bit analog to-digital converters in TSMC-0.18μm 1.8V CMOS technology is presented. The simulation results and layout of the designed CMOS image sensor are presented.

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 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 score0.555
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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.219
Teacher spread0.212 · 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.

Study designSimulation or modeling
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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicCCD and CMOS Imaging SensorsFrench-language works237,207