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Near-field microwave holographic imaging: Target localization and resolution study

2010· article· en· W2020726501 on OpenAlexaff
Maryam Ravan, Reza K. Amineh, Natalia K. Nikolova

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHolographyMicrowave imagingOpticsReflection (computer programming)Iterative reconstructionImage resolutionMicrowaveResolution (logic)PhysicsSIGNAL (programming language)Field (mathematics)Computer scienceComputer visionArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

A new two-dimensional (2D) microwave holographic technique is proposed to reconstruct the 2D image of a target. It is based on the data recorded by two antennas scanning two rectangular parallel apertures on both sides of a target. In this method the reflection coefficients of the antennas are first processed to localize target in the range direction. Then, the 2D image of the target is reconstructed. There is no assumption for the incident field and both the back-scattered and forward-scattered signals can be used to reconstruct the image of the target. This makes the technique applicable to tomographic measurements where the near-field signal transmitted through the target is measured.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.483

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 head0.004
GPT teacher head0.202
Teacher spread0.199 · 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
GenreEmpirical

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
Published2010
Admission routes1
Has abstractyes

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