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Record W2104980687 · doi:10.1109/ccece.2002.1013079

Parallel filtering and thresholding of images on the SIMD DSP-RAM architecture

2003· article· en· W2104980687 on OpenAlexafffund
S.J. Dillen, B.F. Cockburn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSIMDCoprocessorMMXComputer scienceDigital signal processingPentiumParallel computingBenchmark (surveying)Computer hardwareConvolution (computer science)Computer architectureEmbedded systemArtificial intelligence

Abstract

fetched live from OpenAlex

DSP-RAM is a moderately-parallel, single-chip SIMD (single instruction stream, multiple data stream) architecture that has been proposed as a suitable hardware platform for accelerating signal processing applications. Our goal is to evaluate the potential of DSP-RAM as a coprocessor for important low-level graphical operations such as convolution filtering and thresholding. Insights gained during the initial implementation prompted a minor improvement to the original design. The benchmark operations were microcoded for DSP-RAM and then simulated on an architectural simulator written in C++. The simulation results were compared to the measured execution times for the corresponding Intel integrated performance primitives functions running on a conventional 1 GHz Pentium III personal computer A modest 25 MHz DSP-RAM coprocessor was found to give equivalent or superior performance for mid to large-sized image frames.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.711
Threshold uncertainty score0.232

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 science0.0010.000
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 head0.020
GPT teacher head0.264
Teacher spread0.244 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations2
Published2003
Admission routes2
Has abstractyes

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