Hajar Chouhayebi

Papers

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About

Hajar Chouhayebi is a researcher in computer vision and affective computing, with a primary focus on facial expression recognition. Her most cited work, "A dynamic fusion of features from deep learning and the HOG-TOP algorithm for facial expression recognition" (2023), introduces an innovative hybrid approach that combines deep learning features with the HOG-TOP (Histogram of Oriented Gradients from Three Orthogonal Planes) algorithm. This fusion method leverages the strengths of both spatial and temporal feature extraction, enabling more robust and accurate recognition of dynamic facial expressions. By integrating traditional handcrafted features with modern deep learning architectures, Chouhayebi's work addresses key challenges in capturing subtle and transient emotional cues from video sequences. Her research contributes to advancing human-computer interaction, affective computing systems, and real-time emotion analysis. With 6 citations to date, this paper has already garnered attention for its practical and theoretical contributions to the field. Chouhayebi's work stands out for its methodological rigor and potential applications in areas such as mental health monitoring, user experience design, and intelligent surveillance systems.