Salabat Khan
Papers
1
Total Citations
18
H-Index
1
About
Salabat Khan is a computer vision researcher whose work focuses on advancing human-computer interaction through facial expression recognition. His key research areas include deep learning, affective computing, and intelligent visual surveillance systems. Khan's most significant contribution is a lightweight deep learning model for facial expression recognition, published in 2023, which has already garnered 18 citations for its practical approach to classifying seven core emotions—happiness, sadness, anger, fear, contempt, surprise, and disgust. This work addresses critical challenges in real-world applications such as human-robot interaction and behavior analysis by achieving high accuracy without requiring extensive computational resources. Khan's research stands out for its emphasis on deployable, efficient solutions that bridge the gap between academic computer vision and practical surveillance and robotics systems. His work continues to influence the development of more responsive, emotionally aware technologies, making him a promising voice in the field of affective computing and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1Facial expression recognition using lightweight deep learning modeling18 citations · 2023