Papers
2
Total Citations
23
H-Index
2
About
Abdelmalik Taleb‐Ahmed is a computer vision researcher whose work bridges affective computing and industrial automation. His primary research areas include facial expression recognition, warehouse management automation, and the integration of computer vision with hardware prototyping. His most cited paper, "Fusion of transformed shallow features for facial expression recognition" (2019, 18 citations), introduces a novel approach that combines transformed shallow features to improve the accuracy of automatic facial expression recognition systems, which are critical for applications in human-computer interaction, cognitive state analysis, and behavioral understanding. This work highlights his contribution to enhancing the robustness of emotion detection algorithms. More recently, his survey "Computer vision in warehouse management automation: A proposed methods with prototyping hardware" (2025, 5 citations) demonstrates his forward-looking focus on applying vision-based solutions to logistics and supply chain efficiency. Taleb‐Ahmed’s research is notable for its practical orientation, aiming to translate theoretical advances into real-world systems. His work has been cited in contexts ranging from psychology to robotics, underscoring its interdisciplinary impact.
Research Focus
Key Achievements
Top Papers
- 1Fusion of transformed shallow features for facial expression recognition18 citations · 2019
- 2