Jhing-Fa Wang
National Cheng Kung University, Tajen University, Sanda University
Papers
15
Total Citations
165
H-Index
6
About
Jhing-Fa Wang is a leading researcher in intelligent robotics and human-robot interaction, with a focus on developing autonomous systems that can perceive, understand, and assist humans in real-world environments. His work spans speech recognition, computer vision, and mobile robotics, particularly for healthcare and smart home applications. Wang’s most cited paper (72 citations) introduces an attention-based bidirectional LSTM for outpatient text classification, enabling robot-assisted hospital triage to reduce medical resource waste. He has also made significant contributions to noise-robust speech recognition for human-robot interaction, with multiple papers on speech enhancement and noise detection that improve robot command recognition in noisy environments. His research on omnidirectional mobile systems and SLAM-based autonomous navigation has advanced the design of home service robots capable of human following and obstacle avoidance. Wang’s work on human activity recognition using Kinect sensors and deep CNN-based face recognition further demonstrates his commitment to creating perceptive, interactive robots. With a portfolio of papers addressing practical challenges in robot perception, navigation, and human-robot communication, Wang’s research has direct implications for the next generation of assistive and service robots.
Research Focus
Key Achievements
Top Papers
- 1
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- 3Design and Implementation of AMR Robot Based on RGBD, VSLAM and SLAM9 citations · 2021
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- 5VQ-HMM classifier for human activity recognition based on R-GBD sensor8 citations · 2017
- 6Automatic Prescription Recognition System6 citations · 2018
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- 8Fuzzy Obstacle Avoidance for the Mobile System of Service Robots5 citations · 2020
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