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Record W2047534701 · doi:10.1155/2007/21515

Visual Sensor Networks

2007· article· en· W2047534701 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEURASIP Journal on Advances in Signal Processing · 2007
Typearticle
Languageen
FieldEngineering
TopicInfrared Target Detection Methodologies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSession (web analytics)Digital watermarkingMultimediaFocus (optics)Signal processingTelecommunicationsDigital signal processingComputer securityWorld Wide WebImage (mathematics)Artificial intelligenceComputer hardware

Abstract

fetched live from OpenAlex

His current research interests mainly focus on various topics (including security, networking, and signal processing) of multimedia and time-frequency analysis of signals.He organized a special session on multimedia security in the 2nd and 3rd IEEE Pacific-Rim Conference on Multimedia, respectively (2001-2002).He coorganized two special sessions (in the area of media identification and DRM) in the 5th IEEE International Conference on Multimedia and Expo (ICME), 2004.He was a Guest Coeditor of EURASIP Journal on Advances in Signal Processing, special issue on visual sensor network in 2005.He has owned two US patents, two ROC patents, and one Canadian patent in digital watermarking.He has received the Paper Awards many times from the Image Processing and Pattern Recognition Society of Taiwan for his work on data hiding.He was a corecipient of a National Invention and Creation Award in 2004.He is the editor of the book "Multimedia

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.783
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.320
Teacher spread0.300 · 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