MétaCan
Menu
Back to cohort
Record W2133367918 · doi:10.1109/iscas.2003.1206088

VLSI implementation of a real-time video watermark embedder and detector

2003· article· en· W2133367918 on OpenAlexaff
N.J. Mathai, Ali Sheikholeslami, Deepa Kundur

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Steganography and Watermarking Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDigital watermarkingWatermarkComputer scienceDatapathUncompressed videoVery-large-scale integrationDetectorFrame (networking)Application-specific integrated circuitComputer hardwareCMOSFrame rateFast Fourier transformReal-time computingEmbedded systemVideo processingEmbeddingElectronic engineeringComputer visionAlgorithmArtificial intelligenceImage (mathematics)Video trackingEngineering

Abstract

fetched live from OpenAlex

This paper describes the hardware design and implementation of the JAWS (Just Another Watermarking System) embedder and detector for watermarking of realtime uncompressed digital video. Our design employs a floating point datapath, maximizing dynamic range of the FFT, frame filtering, and correlation operations. The design, implemented in a 1.8V, 0.18 /spl mu/m CMOS process with a core area of 3.53 mm/sup 2/, is capable of watermarking video streams at a peak rate of over 3 Mpixels/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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.328
Threshold uncertainty score0.292

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 science0.0000.000
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 head0.009
GPT teacher head0.267
Teacher spread0.258 · 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 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

Citations37
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Steganography and Watermarking TechniquesFrench-language works237,207