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Record W2913468736 · doi:10.1145/3310195.3310204

JPEG column

2019· article· en· W2913468736 on OpenAlexaboutno aff
António Pinheiro

Bibliographic record

VenueACM SIGMultimedia Records · 2019
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsJPEGJPEG 2000Computer scienceCoding (social sciences)Flexibility (engineering)Column (typography)Image qualityData compressionLossless JPEGImage compressionMultimediaComputer visionTelecommunicationsImage processingImage (mathematics)StatisticsMathematics

Abstract

fetched live from OpenAlex

The 81st JPEG meeting was held in Vancouver, British Columbia, Canada, at which significant efforts were put into the analysis of the responses to the call for proposals on the next generation image coding standard, nicknamed JPEG XL, that is expected to provide a solution for image format with improved quality and flexibility, allied with a better compression efficiency. The responses to the call confirms the interest of different parties on this activity. Moreover, the initial subjective and objective evaluation of the different proposals confirm a significative evolution on both quality and compression efficiency that will be provided by the future standard.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.618
Threshold uncertainty score0.545

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.6180.517

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 head0.011
GPT teacher head0.264
Teacher spread0.253 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueACM SIGMultimedia RecordsSame topicAdvanced Data Compression TechniquesFrench-language works237,207