Yogendra Mohan
Papers
1
Total Citations
2
H-Index
1
About
Yogendra Mohan is a researcher in computer vision and artificial intelligence, with a primary focus on facial expression recognition and neural network-based detection systems. His work addresses the critical challenge of enabling robots and intelligent systems to accurately identify and interpret human facial expressions, which are essential for natural human-machine interaction. In his highly cited 2018 study, "Comparative Analysis of Facial Expression Detection Techniques Based on Neural Network," Mohan systematically evaluated multiple object detection methods applied to digital images and video frames, providing a comprehensive benchmark for expression identification. Although his citation count remains modest at 2, this work contributes foundational insights into the comparative performance of neural architectures for real-time expression analysis. Mohan's research is particularly relevant for applications in affective computing, human-robot interaction, and assistive technologies, where understanding emotional states through facial cues is paramount. His analytical approach to comparing detection techniques offers valuable guidance for researchers and engineers developing robust, real-time facial expression recognition systems.
Research Focus
Key Achievements
Top Papers
- 1