Situation-Specific Models of Color Differentiation
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Color is commonly used to represent categories and values in computer applications, but users with Color-Vision Deficiencies (CVD) often have difficulty differentiating these colors. Recoloring tools have been developed to address the problem, but current recolorers are limited in that they work from a model of only one type of congenital CVD (i.e., dichromatism). This model does not adequately describe many other forms of CVD (e.g., more common congenital deficiencies such as anomalous trichromacy, acquired deficiencies such as cataracts or age-related yellowing of the lens, or temporary deficiencies such as wearing tinted glasses or working in bright sunlight), and so standard recolorers work poorly in many situations. In this article we describe an alternate approach that can address these limitations. The new approach, called Situation-Specific Modeling (SSM), constructs a model of a specific user’s color differentiation abilities in a specific situation, and uses that model as the basis for recoloring digital presentations. As a result, SSM can inherently handle all types of CVD, whether congenital, acquired, or environmental. In this article we describe and evaluate several models that are based on the SSM approach. Our first model of individual color differentiation (called ICD-1) works in RGB color space, and a user study showed it to be accurate and robust (both for users with and without congenital CVD). However, three aspects of ICD-1 were identified as needing improvement: the calibration step needed to build the situation-specific model, and the prediction steps used in recoloring were too slow for real-world use; and the results of the model’s predictions were too coarse for some uses. We therefore developed three further techniques: ICD-2 reduces the time needed to calibrate the model; ICD-3 reduces the time needed to make predictions with the model; and ICD-4 provides additional information about the degree of differentiability in a prediction. Our final result is a model of the user’s color perception that handles any type of CVD, can be calibrated in two minutes, and can find replacement colors in near-real time ( ~ 1 second for a 64-color image). The ICD models provide a tool that can greatly improve the perceptibility of digital color for many different types of CVD users, and also demonstrates situation-specific modeling as a new approach that can broaden the applicability of assistive technology.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle