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Record W2000525729 · doi:10.1109/isbmsb.2010.5463161

Evaluation of H.264/AVC error resilience in HD IPTV applications

2010· article· en· W2000525729 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsIPTVComputer scienceVideo qualityDecoding methodsHigh-definition televisionDigital subscriber lineChannel (broadcasting)Scalable Video CodingComputer networkReal-time computingTelecommunicationsArtificial intelligenceMotion compensation

Abstract

fetched live from OpenAlex

The delivery of High Definition Television (HDTV) over IP networks, namely the HD IPTV, has emerged as one of the major distribution and access techniques for broadband multimedia services. IPTV adopts H.264/AVC as its coding standard due to its high video compression efficiency as well as powerful error resilience features. This paper presents studies on some of these features applied to HD IPTV applications. A test system is deployed to simulate the delivery of HD video over a DSL based IPTV network. Effects of error resilience of slicing and Instantaneous Decoding Refreshing (IDR) features on video quality are examined in both channel non-impaired and channel impaired with burst noise circumstances. Based on the acquired results, optimal slice size was obtained for HD video transmission over an impaired channel. The quality of experience related to the IDR interval in combating error propagation was also characterized.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.049
GPT teacher head0.336
Teacher spread0.287 · 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