Mesure du contraste local dans les images, application à la mesure de distance de visibilité par caméra embarquée
Bibliographic record
Abstract
A partir de la definition de la distance de visibilite meteorologique, nous definissons les distances de visibilite mobilisee et mobilisable. Cela nous conduit a proposer une methode generique de mesure de la distance de visibilite atmospherique par camera embarquee a bord d'un vehicule. Celle-ci consiste a rechercher l'objet le plus eloigne ayant un contraste d'au moins 5%. Nous detaillons dans cet article comment estimer le contraste. Pour ce faire, nous presentons une methode precise, robuste et rapide issue de la technique de segmentation d'images de Kohler. Nous montrons comment nous avons adapte cette methode a nos besoins. Pour justifier nos propos, nous comparons notre approche aux techniques de Gordon et Beghdadi. Nous appliquons le resultat a la mesure de distance de visibilite en fusionnant notre mesure de contraste local avec une information de distance obtenue par stereovision. Nous finissons par donner des exemples de mesure de distance de visibilite mobilisee sous differentes conditions meteorologiques.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".