MétaCan
Menu
Back to cohort
Record W2162043916 · doi:10.1109/ccece.2004.1345271

Hardware implementation of the optimized transform and quantization blocks of H.264

2004· article· en· W2162043916 on OpenAlexaff
Roman C. Kordasiewicz, Shahram Shirani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComputer scienceField-programmable gate arrayQuantization (signal processing)SoftwareVirtexComputer hardwareDiscrete cosine transformCoding (social sciences)Transform codingEmbedded systemOperating systemImage (mathematics)AlgorithmArtificial intelligence

Abstract

fetched live from OpenAlex

H.264 also known as MPEG-4 part 10 or JVT, is a new video coding standard that is extremely efficient and is poised to appear in the next generation of HD-DVD players and recorders. This paper presents one of the first hardware architectures of the transform and quantization blocks, which are incorporated into a software/hardware system implemented on a Virtex II Pro FPGA. This implementation focuses on eliminating drift effects, multiply free and low gain transform, and reducing memory bandwidth. A large system on a programmable chip was developed. It uses a Power PC (PPC) to run a software program to optionally perform DCT and quantization in both the software and hardware. This paper presents DCT and quantization blocks that can process about 1500 Mpixel/s, and a system that can process about 0.8 Mpixel/s.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0050.002

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 head0.269
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations38
Published2004
Admission routes1
Has abstractyes

Explore more

Same topicVideo Coding and Compression TechnologiesFrench-language works237,207