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Record W3008680146 · doi:10.1117/12.2545382

Augmented reality, 3D measurement, and thermal imagery for computer-assisted manufacturing

2020· article· en· W3008680146 on OpenAlexaff
Jonathan Boisvert, Marc-Antoine Drouin, Guy Godin, Michel Picard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAugmented realityProjectorComputer scienceContext (archaeology)Component (thermodynamics)Projection (relational algebra)Computer visionModalArtificial intelligenceComputer graphics (images)Materials science

Abstract

fetched live from OpenAlex

One of the challenges in high-precision manufacturing is constant inspection as well as efficient communication of the inspection results to the workers. In this context, we are presenting a multi-modal 3D imaging system designed for computer-assisted assembly manufacturing using augmented reality. The three-dimensional measurement subsystem is a structured-light system based on a digital micro-mirror device (DMD). The augmented reality imagery is displayed on the components being manufactured using another DMD-based color projector that uses wavelengths that do not interfere with the 3D measurements. A thermal camera is also part of the system and calibrated with respect to the measurement and projection subsystems. In typical target usage, the system can display localized shape deviation with respect to nominal values, or the surface temperature across the component, or any information obtained or derived from the subsystems. Moreover, it can be used to display assembly instructions and validate the compliance of the final manufactured component.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score0.577

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 head0.092
GPT teacher head0.275
Teacher spread0.183 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2020
Admission routes1
Has abstractyes

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