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Record W2077411269 · doi:10.1117/12.596811

A hardware architecture for a context-adaptive binary arithmetic coder

2005· article· en· W2077411269 on OpenAlex

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

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceContext-adaptive binary arithmetic codingArithmetic codingEncoderContext-adaptive variable-length codingData compressionEntropy encodingComputer hardwareAdaptive codingField-programmable gate arrayBinary numberParallel computingENCODEEncoding (memory)Computer architectureArithmeticAlgorithmLossless compressionArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

The H.264 video compression standard uses a context-adaptive binary arithmetic coder (CABAC) as an entropy coding mechanism. While the coder provides excellent compression efficiency, it is computationally demanding. On typical general-purpose processors, it can take up to hundreds of cycles to encode a single bit. In this paper, we propose an architecture for a CABAC encoder that can easily be incorporated into system-on-chip designs for H.264 compression. The CABAC is inherently serial and we divide the problem into several stages to derive a design that can provide a throughput of two cycles per encoded bit. The engine proposed is capable of handling binarization of the syntactical elements and provides the coded bit-stream via a first-in first-out buffer. The design is implemented on an Altera FPGA platform that can run at 50 MHz enabling a 25 Mbps encoding rate.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.016
GPT teacher head0.232
Teacher spread0.217 · 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