Company Filing History:
Years Active: 2022-2024
Title: Innovations of Yu-Feng Wu
Introduction
Yu-Feng Wu is a notable inventor based in Zhubei, Taiwan. He has made significant contributions to the field of gesture recognition technology. With a total of 2 patents, his work focuses on enhancing user interaction through innovative methods and systems.
Latest Patents
Yu-Feng Wu's latest patents include an impulse-like gesture recognition method and an impulse-like gesture recognition system. The performing device of the impulse-like gesture recognition system executes an impulse-like gesture recognition method. This method involves receiving a sensing signal from a sensing unit, determining a prediction with at least one impulse-like label using a deep learning-based model, and classifying at least one gesture event based on the prediction. This classification helps in determining the user's motion. The use of impulse-like labels ensures that the detection score is non-decreasing, allowing for fast reaction times to incoming gestures and easy decomposition of rapid consecutive gestures without the need for expensive post-processing.
Another significant patent is the range Doppler angle detection method and device. This method includes steps such as receiving first and second sensing signals, performing 1D and 2D Fast Fourier Transforms (FFT) on these signals, and calculating a range Doppler angle. This innovation reduces the computational load of the gesture recognition function, making it more efficient.
Career Highlights
Yu-Feng Wu is currently employed at Kaikutek Inc., where he continues to develop cutting-edge technologies in gesture recognition. His work is instrumental in advancing the capabilities of interactive devices.
Collaborations
He collaborates with talented coworkers, including Mike Chun-Hung Wang and Chun-Hsuan Kuo, contributing to a dynamic and innovative work environment.
Conclusion
Yu-Feng Wu's contributions to gesture recognition technology exemplify the impact of innovative thinking in enhancing user interaction. His patents reflect a commitment to improving the efficiency and effectiveness of gesture recognition systems.