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Record W4240265971 · doi:10.1109/icpr.2004.1334379

Prioritized region of interest coding in JPEG2000

2004· article· en· W4240265971 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

VenueProceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. · 2004
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsENCODEJPEG 2000Computer scienceRegion of interestCoding (social sciences)Multiple description codingNetwork packetArtificial intelligenceComputer visionAlgorithmImage compressionDecoding methodsImage (mathematics)Image processingComputer networkMathematicsStatistics

Abstract

fetched live from OpenAlex

A method is proposed to encode multiple regions of interest in the JPEG2000 image-coding framework. The algorithm is based on the rearrangement of packets in the code-stream to place the regions of interest before the background coefficients. In order to improve the quality of the reconstructed image, partial background information is included with the regions of interest. The proposed technique is fully compatible with the current JPEG2000 standard and allows transmission of different regions of interest with different priorities. Experimental results demonstrating the validity of the proposed approach are presented and compared with existing region of interest coding techniques.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.899

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 communication0.0000.001
Open science0.0020.000
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 head0.099
GPT teacher head0.308
Teacher spread0.209 · 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