MétaCan
Menu
Back to cohort
Record W4409581411 · doi:10.1109/mgrs.2025.3554979

Video Synthetic Aperture Radar Techniques: <i>A retrospective and prospective overview</i>

2025· article· en· W4409581411 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Geoscience and Remote Sensing Magazine · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced SAR Imaging Techniques
Canadian institutionsUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsSynthetic aperture radarRemote sensingRadar imagingGeologyInverse synthetic aperture radarRadarComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Video synthetic aperture radar (VideoSAR) describes detailed spatial-temporal echo-location signals as representative of the emerging microwave camera for dynamic observation in remote sensing community. Over the past decade, extensive techniques have sprung up for efforts related to this topic. This article summarizes a bird’s-eye overview of VideoSAR techniques into three categories, with emphasis on typical system development, persistent frame imaging, and information extraction. Furthermore, potential future directions of VideoSAR technologies are provided on possible application scenarios.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.559
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.237
Teacher spread0.231 · 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