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Record W2148642242 · doi:10.1109/tcsvt.2005.846429

A new time distributed DCT architecture for MPEG-4 hardware reference model

2005· article· en· W2148642242 on OpenAlexaff
Mehboob Alam, Wael Badawy, G.A. Jullien

Bibliographic record

VenueIEEE Transactions on Circuits and Systems for Video Technology · 2005
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDiscrete cosine transformComputer scienceComputationRedundancy (engineering)ArchitectureScheduling (production processes)Coefficient matrixExploitTransform codingAlgorithmParallel computingComputer hardwareEmbedded systemMathematicsArtificial intelligenceImage (mathematics)

Abstract

fetched live from OpenAlex

This paper presents the design of a new time distributed architecture (TDA) which outlines the architecture (ISO/IEC JTC1/SC29/WG11 MPEG2002/M8565) submitted to MPEG4 Part9 committee and included in the ISO/IEC JTC1/SC29/WG11 MPEG2002/9115N document. The proposed TDA optimizes the two-dimensional discrete cosine transform (2-D-DCT) architecture performance. It uses a time distribution mechanism to exploit the computational redundancy within the inner product computation module. The application specific requirements of input, output and coefficients word length are met by scheduling the input data. The coefficient matrix uses linear mappings to assign necessary computation to processor elements in both space and time domains. The performance analysis shows performance savings in excess of 96% as compared to the direct implementation and more than 71% as compared to other optimized application specific architectures for DCT.

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: Simulation or modeling · 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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.027
GPT teacher head0.272
Teacher spread0.245 · 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 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

Citations22
Published2005
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Circuits and Systems for Video TechnologySame topicAdvanced Data Compression TechniquesFrench-language works237,207