Structure Prétopologique et Applications
Bibliographic record
Abstract
Ce livre presente un ensemble d’applications des structures pretopologiques en reconnaissance de formes et plus particulierement pour l’extraction de l’ecriture de documents presentant des images de scenes et pour la verification hors ligne des signatures manuscrites. Les travaux ont ete realise entre 1997 et 2010 dans le cadre d’une collaboration entre le laboratoire Image et Reconnaissance de Formes – Systemes Intelligents et Communicants (IRF – SIC) de l’Universite Ibn Zohr d’Agadir (Maroc) et le laboratoire Interdisciplinaire de Recherche en Imagerie et Calcul Scientifique (LIRICS) de l’Universite du Quebec a Trois-Rivieres, Quebec (Canada). Cette collaboration adonne suite a la soutenance de deux doctorats d’etat et un nombre important de publications et de projets de recherche finances.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.016 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".