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Record W7005712525

Ship Detection Performance Predictions for Next Generation Spaceborne Synthetic Aperture Radars

2001· article· en· W7005712525 on OpenAlexaboutno aff

Bibliographic record

VenueDefense Technical Information Center (DTIC) · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEthnobotanical and Medicinal Plants Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSynthetic aperture radarSatelliteSide looking airborne radarRadar imagingInverse synthetic aperture radarRadarPosition (finance)Early-warning radarSpace-based radar
DOInot available

Abstract

fetched live from OpenAlex

Following success in other areas as a remote sensor, the spaceborne microwave image radars are assuming a notable position in the problem of ship detection for civilian and military purposes. This work will discuss the strong and weak points of Synthetic Aperture Radar (SAR) when used for ship detection. First, the thesis gives a brief description of SAR fundamentals, image processing and the parameters for ship detection. Second, the actual techniques, limitations, errors and some models used for ship detection are described. Finally, using a well-known and reliable ship detection model (Vachon et al. 1997), tested in the Canadian Ocean Monitoring Workstation and in some validation field programs, the new generation of spaceborne SARs, mainly RADARSAT 2, are analyzed for ship detection capabilities. During the analysis parameters like wind velocity, wind direction related to the antenna, satellite incident angle and Number of Looks are changed to study their influence on ship detection.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score0.357

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 communication0.0000.001
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 head0.061
GPT teacher head0.241
Teacher spread0.179 · 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 designNot applicable
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

Citations0
Published2001
Admission routes1
Has abstractyes

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