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Record W2169728719 · doi:10.1109/igarss.2012.6352487

All optical Synthetic Aperture Lidar sensing-to-processing chain based on SAR technology

2012· article· en· W2169728719 on OpenAlexaff
Linda Marchese, Simon Turbide, Marc Terroux, Alain Bergeron

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsInstitut National d'Optique
Fundersnot available
KeywordsSynthetic aperture radarLidarPayload (computing)Computer scienceRemote sensing3D optical data storageAperture (computer memory)Data processingImage resolutionComputer visionArtificial intelligenceOpticsGeologyEngineeringPhysics

Abstract

fetched live from OpenAlex

Synthetic Aperture Lidar (SAL) is an emerging technology that has the potential to offer high resolution images from space with a compact payload. This paper presents a unique synthetic aperture lidar system prototype system that is all optical. That is, not only is the data collection system optical (fiber based), but the data processing is also performed optically (using sets of lenses). Such a compact fully integrated all-optical system would be ideal for image capture and processing to be performed nearly simultaneously on-board. The final high resolution images could be thus directly downlinked to operation users in a timely fashion.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.695
Threshold uncertainty score0.865

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)0.0000.000

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 head0.259
Teacher spread0.248 · 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 designOther design
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

Citations2
Published2012
Admission routes1
Has abstractyes

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