Hamid Tairi

Sidi Mohamed Ben Abdellah University, Agence pour le Développement et la Réhabilitation de la Ville de Fès

Papers

Total Citations

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About

Hamid Tairi’s research bridges computer vision and artificial intelligence, with a focus on optical flow estimation, facial expression recognition, and intelligent automation. His early work on “Optical flow estimation based on the structure–texture image decomposition” (2015, 8 citations) introduced a novel approach that separates image components to improve motion analysis accuracy, laying groundwork for robust visual tracking. Tairi later advanced affective computing with “A dynamic fusion of features from deep learning and the HOG-TOP algorithm for facial expression recognition” (2023, 6 citations), demonstrating how hybrid models can enhance emotion detection in challenging conditions. Most recently, his forward-looking review “Intelligent Agents in Smart Logistics and Warehouse Automation: Overview” (2025, 2 citations) synthesizes the transformative role of AI in supply chain management, highlighting agent-based systems that optimize real-time decision-making. Tairi’s contributions span foundational image processing techniques to applied AI solutions, with his work cited across disciplines from robotics to human-computer interaction. His ability to integrate classical algorithms with modern deep learning reflects a career dedicated to solving practical problems through computational intelligence.