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High Resolution Stereo Camera (HRSC)-Multispectral 3D-Data Acquisition and Photogrammetric Data Processing

2000· article· en· W1982108231 on OpenAlexvenueno aff
F. Wewel, F. Scholten, K. Gwinner

Bibliographic record

VenueCanadian Journal of Remote Sensing · 2000
Typearticle
Languageen
FieldEngineering
TopicSatellite Image Processing and Photogrammetry
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesCartographyGeologyGeographyArt

Abstract

fetched live from OpenAlex

La caméra HRSC (High Resolution Stereo Camera) a été conçue au départ pour l'exploration de la planète Mars dans le cadre de la mission spatiale internationale Mars96. Au cours des dernières années, une version aéroportée de la caméra. HRSC-A, a été utilisée avec succès au cours de diverses campagnes aéroportées pour l'observation de la Terre. Les résultats et les produits dérivés au cours de ces expériences démontrent le potentiel unique de cette caméra pour une variété d'application grâce à son haut niveau technologique. Jumelée au système haute technologie GPS/INS de la compagnie APPLANIX Corporation, qui fournit une localisation et un pointage très précis en cours de vol. on peut générer des images et des produits 3-D avec une précision relative d'environ 10–15 cm et une précision absolue d'environ 20–25 cm. à partir d'une altitude de 3 000 m. En combinaison avec son logiciel de traitement photogrammétrique, elle constitue le premier système mondial opérationnel entièrement automatisé d'acquisition d'images numériques multispectrales et à haute résolution et d'imagerie 3-D dans cette nouvelle ère de la photogrammétrie.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.004

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 head0.026
GPT teacher head0.242
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations45
Published2000
Admission routes1
Has abstractyes

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