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Record W1730086933

A SWIR hyperspectral imaging system for art history and art conservation

2011· book-chapter· en· W1730086933 on OpenAlexfundno aff
Haïda Liang, Kafing Keita, C.N. Pannell, Jon Ward

Bibliographic record

VenueRUA, Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante) · 2011
Typebook-chapter
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilTrent UniversityNottingham Trent University
KeywordsHyperspectral imagingMultispectral imageRemote sensingInfraredPaintingImaging spectrometerOpticsComputer scienceGeologySpectrometerPhysicsArt
DOInot available

Abstract

fetched live from OpenAlex

PRISMS is a portable hyperspectral imaging system designed for high resolution, in situ, remote imaging of paintings at inaccessible heights from the ground level. It currently operates from 400nm to 1700nm to provide detailed conservation monitoring, material identification and to assist art historical investigations for wall paintings. The system can be fitted with a variety of imagers to operate in the visible, near infrared and short wave infrared at close range and remotely. This talk will focus on the SWIR (short wave infrared) hyperspectral imager and its applications in art history and art conservation. The filtering system in the SWIR is based on an AOTF (acousto-optical tunable filter) system developed by Gooch & Housego that operates between 900nm and 1700nm which provides fast switching between the spectral bands as well as full flexibility in terms of central wavelength and bandwidth of the filters. Applications in imaging of underdrawings (preparatory sketches) beneath oil paintings and identification of paint materials will be presented.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.196
Teacher spread0.188 · 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.

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

Citations5
Published2011
Admission routes1
Has abstractyes

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