This article analyzes modern methods and algorithms for the automatic recognition of humanemotions through facial expressions. The study examines the processes of facial expression identificationbased on the Facial Action Coding System (FACS). The possibilities of detecting emotional states, includingexcitement, confusion, concentration, and nervousness, through the identification of facial landmark points andthe distances between them are discussed. Furthermore, the effectiveness of using the Tree-Augmented NaiveBayes (TAN) classifier and the CK+ database in facial expression analysis is investigated.The article also proposes a semantic model of an automated facial expression recognition system andsubstantiates its significance in the educational process, particularly in improving authentication and monitoringsystems within electronic learning platforms. The proposed system enables continuous monitoring of students’emotional states, enhances security during examination processes, and automates personal identificationprocedures.
| Mualliflar | Maxamadov , Rustam, Djamatov , Mustafa |
|---|---|
| Jurnal | Innovation science and technologiy |
| Nashr sanasi | 2026-05-01 |
| Jild | 2 |
| Son | 5 |
| Til | Ingliz |
| DOI | 10.5281/zenodo.20496996 |
DOI: 10.5281/zenodo.20496996 · Maqolaning asl sahifasi
Facial expression recognition, emotion recognition, Facial Action Coding System (FACS), Action Units (AU), facial landmarks, biometric identification, Tree-Augmented Naive Bayes (TAN) classifier, CK+ database, artificial intelligence, computer vision, human-computer interaction, e-learning, authentication, facial movement analysis, emotional state monitoring.
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