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Intersecting Color Manifolds

2011· article· en· W2399177186 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

VenueColor and Imaging Conference · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicColor Science and Applications
Canadian institutionsBurnaby Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStandard illuminantRGB color modelArtificial intelligenceComputer visionComputer scienceColor spaceRGB color spaceIntersection (aeronautics)Manifold (fluid mechanics)ChromaticityMathematicsColor imageImage (mathematics)Image processingGeography

Abstract

fetched live from OpenAlex

Logvinenko's color atlas theory provides a structure in which a complete set of color-equivalent material and illumination pairs can be generated to match any given input RGB color. In chromaticity space, the set of such pairs forms a 2-dimensional manifold embedded in a 4-dimensional space. For singleilluminant scenes, the illumination for different input RGB values must be contained in all the corresponding manifolds. The proposed illumination-estimation method estimates the scene illumination based on calculating the intersection of the illuminant components of the respective manifolds through a Hough-like voting process. Overall, the performance on the two datasets for which camera sensitivity functions are available is comparable to existing methods. The advantage of the formulating the illumination-estimation in terms of manifold intersection is that it expresses the constraints provided by each available RGB measurement within a sound theoretical foundation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.688

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.249
Teacher spread0.218 · 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