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Record W2105384445 · doi:10.1109/bsc.2010.5472949

Two-dimensional barcodes for mobile phones

2010· article· en· W2105384445 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
TopicQR Code Applications and Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBarcodeComputer scienceCamera phoneCode (set theory)Discrete cosine transformMobile phoneComputer visionChannel (broadcasting)Process (computing)ExploitArtificial intelligenceDomain (mathematical analysis)Noise (video)Computer graphics (images)Image (mathematics)TelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Motivated by a number of potential applications for a high data-density barcode that can be easily photographed and decoded by mobile phones, this paper presents the design of a new colour high data-density two-dimensional barcode symbology. The new symbology is designed to exploit the low-pass characteristic of a camera phone channel, and encodes information in the spatial Discrete Cosine Transform domain. A water-filling process and a noise-shaping algorithm enhance performance, while a new fast acquisition method allows for rotational and size invariance. An outer Accumulate-Repeat-Accumulate code is employed, followed by an inner Reed Muller code with a rate varying according to spatial frequency. The final barcode data-density is 3.5 times greater than the leading symbology and has proven robust to various impairments imposed by camera phones.

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: Methods · Consensus signal: none
Teacher disagreement score0.641
Threshold uncertainty score0.157

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 science0.0010.000
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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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

Quick stats

Citations12
Published2010
Admission routes1
Has abstractyes

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Same topicQR Code Applications and TechnologiesFrench-language works237,207