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Record W2123862616 · doi:10.1109/hpcc.2011.58

Complexity Control Scheme for H.264/AVC Inter Frame Encoding

2011· article· en· W2123862616 on OpenAlexaff
Xingang Liu, Laurence T. Yang, Kwanghoon Sohn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsMacroblockComputer scienceEncoding (memory)EncoderScalable Video CodingCoding (social sciences)Context-adaptive variable-length codingReal-time computingContext-adaptive binary arithmetic codingFrame (networking)Computational complexity theoryCoding tree unitIntra-frameInter frameScheme (mathematics)AlgorithmReference frameDecoding methodsData compressionMotion compensationComputer networkArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

In this paper, a complexity control scheme (CCS) for Inter frame mode decision (MD) is proposed for H.264/AVC encoder to speed-up the original encoding process. The information extracted from macroblock (MB), which can be used to pre-estimate the optimal mode of the MB is investigated and utilized to eliminate the redundant mode candidates. The simulation results show that the proposed algorithm can reduce over 80% Inter frame encoding time with little quality loss. It can be widely implemented in the mobile communication systems with H.264/AVC standard to realize the real-time video signal coding.

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)0.002
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.140
GPT teacher head0.283
Teacher spread0.143 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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