J
Jeen-Shing Wang
Researcher at National Cheng Kung University
Publications - 112
Citations - 3471
Jeen-Shing Wang is an academic researcher from National Cheng Kung University. The author has contributed to research in topics: Recurrent neural network & Cluster analysis. The author has an hindex of 25, co-authored 112 publications receiving 2996 citations. Previous affiliations of Jeen-Shing Wang include University of Missouri & Purdue University.
Papers
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Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers
TL;DR: This paper presents a systematic design approach for constructing neural classifiers that are capable of classifying human activities using a triaxial accelerometer and adopts neural networks as the classifiers for activity recognition.
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Self-adaptive neuro-fuzzy inference systems for classification applications
Jeen-Shing Wang,C.S.G. Lee +1 more
TL;DR: This paper presents a self- Adaptive neuro-fuzzy inference system (SANFIS) that is capable of self-adapting and self-organizing its internal structure to acquire a parsimonious rule-base for interpreting the embedded knowledge of a system from the given training data set.
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Automatic sleep stage recurrent neural classifier using energy features of EEG signals
TL;DR: The result demonstrates that the proposed recurrent neural classifier using the energy features extracted from characteristic waves of EEG signals can classify sleep stages more efficiently and accurately using only a single EEG channel.
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Self-adaptive recurrent neuro-fuzzy control for an autonomous underwater vehicle
Jeen-Shing Wang,C.S.G. Lee +1 more
TL;DR: This paper presents the utilization of a self-adaptive recurrent neuro-fuzzy control as a feedforward controller and a proportional-plus-derivativecontrol as a feedback controller for controlling an autonomous underwater vehicle (AUV) in an unstructured environment.
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An Accelerometer-Based Digital Pen With a Trajectory Recognition Algorithm for Handwritten Digit and Gesture Recognition
Jeen-Shing Wang,Fang-Chen Chuang +1 more
TL;DR: The experimental results have successfully validated the effectiveness of the trajectory recognition algorithm for handwritten digit and gesture recognition using the proposed digital pen.