MétaCan
Menu
Back to cohort
Record W2010018825 · doi:10.1117/12.541637

A proof-of-concept optical tripwire detector

2004· article· en· W2010018825 on OpenAlexafffund
John E. McFee, Steve Achal, Tyler Ivanco, Ashley P. Tam, Greg Baker, C. D. Anger

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldEngineering
TopicInfrared Target Detection Methodologies
Canadian institutionsItres (Canada)Defence Research and Development Canada
FundersDefence Research and Development Canada
KeywordsDetectorComputer scienceProof of conceptTelecommunications

Abstract

fetched live from OpenAlex

There are currently no fielded technologies for noncontact detection of tripwires. Itres Research Ltd. and DRDC Suffield have been conducting research on optical detection of tripwires since 1996, both for hand-held and vehicle-mounted roles. A proof-of-concept brassboard imager, initially for a vehicle-mounted role, has been constructed. The imager uses a high spatial resolution, panchromatic focal plane array whose high degree of integration includes on-board digitization and flexible addressing capabilities for windowing and subimaging. Command, control and signal processing are accomplished by a computer, based on dual 1GHz Pentium III processors. Using a high level, rapid prototyping language, 1 image frame can be processed in 3 seconds. Straightforward improvements should allow true real-time operation to be achieved. Preliminary testing of the imager was conducted in the outdoor DRDC Suffield Mine Pen in January 2003. Taut, sagging and undulating tripwires of various materials were partially hidden, often nearly invisible to the naked eye, in a number of types of local vegetation. Preliminary, quasi-real-time results showed that many of the wires were detected, although a significant number of false alarms occurred. As expected with the present algorithm, sagging, undulating and highly obscured wires were often difficult to detect. The instrument, results of the trial, planned improvements and future research will be discussed.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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

Citations0
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicInfrared Target Detection MethodologiesFrench-language works237,207