Lamri H.
La Syntaxe Entre L’ordre Linguistique Et Le Désordre Textuel. Linguistique Appliquée [Internet]. 2021;5 (2) :411-422.
Publisher's VersionAbstract
De la phrase au texte, nos élèves souffrent, jusqu'à aujourd'hui, de la méthode d’enseignement adoptée dans nos classes, des dizaines de polycopiés leur sont distribués, tout un tas de papiers écrits en noir, qu’ils essaient de s'en débarrasser au jour le jour pendant la période des examens. L'élève, tenant ces polycopiés, n'a conscience que du nombre de pages, ou des relations paratactiques des tas de phrases, alors que, pour la majorité, l'ordre pédagogique de ce produit écrit est loin, voire impossible d’y parvenir. Les élèves, voire la majorité des enseignants, ne se rendent pas compte que le texte, en tant que forme achevée et fermée, s'avère être dotée d'un système d'information ouvert fermé, et que la phrase est une unité complète de sens et de référence, et un cadre d'analyse de toutes les marques formelles dont la fonction est d'indiquer la structure informationnelle.
Soltani O, BENABDELKADER SOUAD.
Euclidean Distance Versus Manhattan Distance for New Representative SFA Skin Samples for Human Skin Segmentation. Traitement du Signal. 2021.
Abstract
The human color skin image database called SFA, specifically designed to assist research in the area of face recognition, constitutes a very important means particularly for the challenging task of skin detection. It has showed high performances comparing to other existing databases. SFA database provides multiple skin and non-skin samples, which in various combinations with each other allow creating new samples that could be useful and more effective. This particular aspect will be investigated, in the present paper, by creating four new representative skin samples according to the four rules of minimum, maximum, mean and median. The obtained samples will be exploited for the purpose of skin segmentation on the basis of the well-known Euclidean and Manhattan distance metrics. Thereafter, performances of the new representative skin samples versus performances of those skin samples, originally provided by SFA, will be illustrated. Simulation results in both SFA and UTD (University of Texas at Dallas) color face databases indicate that detection rates higher than 92% can be achieved with either measure.
Soltani O, BENABDELKADER SOUAD.
Euclidean Distance Versus Manhattan Distance for New Representative SFA Skin Samples for Human Skin Segmentation. Traitement du Signal. 2021.
Abstract
The human color skin image database called SFA, specifically designed to assist research in the area of face recognition, constitutes a very important means particularly for the challenging task of skin detection. It has showed high performances comparing to other existing databases. SFA database provides multiple skin and non-skin samples, which in various combinations with each other allow creating new samples that could be useful and more effective. This particular aspect will be investigated, in the present paper, by creating four new representative skin samples according to the four rules of minimum, maximum, mean and median. The obtained samples will be exploited for the purpose of skin segmentation on the basis of the well-known Euclidean and Manhattan distance metrics. Thereafter, performances of the new representative skin samples versus performances of those skin samples, originally provided by SFA, will be illustrated. Simulation results in both SFA and UTD (University of Texas at Dallas) color face databases indicate that detection rates higher than 92% can be achieved with either measure.