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Record W2069477605 · doi:10.1109/cicc.2006.320945

ViPro: Focal-Plane Spatially-Oversampling CMOS Image Compression Sensor

2006· article· en· W2069477605 on OpenAlexaff
Ashkan Olyaei, Roman Genov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOversamplingPixelQuantization (signal processing)Discrete cosine transformCardinal pointComputer scienceArtificial intelligenceComputer visionData compressionCMOSFrame rateAlgorithmElectronic engineeringEngineeringImage (mathematics)OpticsPhysics

Abstract

fetched live from OpenAlex

The CMOS image sensor computes spatially-compressing convolutional transforms directly on the focal plane, yielding digital output at a rate proportional to the mere information rate of the video. A bank of column-parallel DeltaSigma-modulated analog-to-digital converters (ADCs) performs distributed columnwise focal-plane oversampling of a set of adjacent pixels and concurrent weighted average quantization. The number of samples per pixel and switched capacitor sampling sequence order set the amplitude and sign of the respective pixel coefficient. Outputs of a set of adjacent ADCs are accumulated to realize a two-dimensional block matrix transform in parallel for all columns. The 3.1 mm times 1.9 mm prototype, ViPro, containing a 128times128 active pixel array and a bank of 128 hybrid algorithmic DeltaSigma-modulated ADCs yields 4 GMACS (multiply-and-accumulates per second) computational throughput in real-time discrete cosine transform (DCT) video compression when scaled to HDTV 1080i resolution

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.663

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)0.0000.000

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 head0.005
GPT teacher head0.195
Teacher spread0.189 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

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