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Robust H.264 Video Decoding Using Crc-Based Single Error Correction And Non-Desynchronizing Bits Validation

2020· article· en· W3089830929 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCyclic redundancy checkDecoding methodsComputer scienceRedundancy (engineering)Network packetError detection and correctionResidualAlgorithmBinary numberBurst errorForward error correctionBit error rateMathematicsArithmeticComputer network

Abstract

fetched live from OpenAlex

In this paper, we introduce a novel cyclic redundancy check (CRC)-based single error correction method which we apply to robust H.264 Baseline video decoding. Unlike state-of-the-art methods, the proposed correction algorithm does not require lookup tables as it determines the error location based on binary operations using the computed link layer CRC syndrome. Since multiple errors can lead to the same CRC syndrome as a single error, verification of the corrected packet is performed through a non-desynchronizing bits validation (NDBV), which forwards only compliant packets to the video decoder. Simulations on the H.264 Baseline profile show an average gain of 3.04 dB and 2.36 dB over state-of-the-art spatio-temporal error concealment (STBMA) and NDBV + STBMA reconstruction methods, respectively, at a residual bit error rate of $10^{-6}$.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.682
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.121
GPT teacher head0.266
Teacher spread0.145 · 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