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This work presents the building and validating of a face expression database and a face expression recognizer. The face expression recognizer uses a geometric-based technique that measures distances between the central point on the face and other 68 facial landmark points. These measures are transformed into features to train a support vector machine. The database was built inside an educational context...
This paper presents two software systems for visual affect and learning styles recognition. The first system recognizes Paul Ekman's seven basic emotions in student expressions which are surprise, fear, disgust, anger, happiness, sadness, and neutral. The second system recognizes the student learning style using the Felder-Silverman Model. Both systems are integrated into an intelligent tutoring system...
We present Fermat, an Intelligent Social Network for Mathematics Learning, which integrates an Intelligent Tutoring System as an extra feature to help students to improve the teaching and learning process. The intelligent tutor takes into account both cognitive and affective aspects. The social network and the affective tutoring systems are accessed from the web. Initial results in math show the benefits...
Integrating teaching with students' emotions is seeking to optimize the learning of these students. This paper presents a learning system which combines different technologies like a learning social network or knowledge society, an authoring tool to produce intelligent tutoring systems and a system for emotion recognition. The recognition of affection or emotions is through modular neural networks...
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