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查看斯高帕斯 (Scopus) 概要
楊 世宏
副教授
機械工程學系
電話
886 6 2757575 ext 62171
電子郵件
vssyang
gs.ncku.edu
tw
網站
https://nckunclab.wixsite.com/neuralcomputationlab
h-index
255
引文
8
h-指數
按照存儲在普爾（Pure）的出版物數量及斯高帕斯（Scopus）引文計算。
2009
2024
每年研究成果
概覽
指紋
網路
專案
(3)
研究成果
(32)
類似的個人檔案
(1)
監製作品
(1)
指紋
查看啟用 Shih-Hung Yang 的研究主題。這些主題標籤來自此人的作品。共同形成了獨特的指紋。
排序方式
重量
按字母排序
Keyphrases
Motor Imagery Decoding
24%
Sequence Imputation
24%
Fall Prediction
24%
Network Model
24%
Subthalamic
24%
Neuro-inspired
24%
Neuronal Signals
24%
Brain Lateralization
24%
Central Thalamus
24%
Local Field Potential Oscillations
24%
Hand Segmentation
24%
Robot Trajectory Tracking
24%
Neuron Evolution
24%
Grey Neural Network
24%
Neural Network
24%
Instrumented Glove
24%
Hand Exoskeleton
24%
Robotic Applications
24%
Cerebrovascular Function
24%
Ensemble Activity
24%
Multimodal Optical Imaging
24%
Theta Phase Precession
24%
Relative Payoffs
24%
Dynamic-Q
24%
Instrumental Learning
24%
Ureido
24%
Goal-directed Reaching
24%
Dodecanoic Acid
24%
Graphene Oxide Paper
24%
Exoskeleton Rehabilitation Robot
24%
Modulatory Interaction
24%
Feedforward Neural Network
24%
Sliced Inverse Regression
24%
Forelimb Movement
24%
Neuronal Spikes
24%
Vertical Disparity
24%
Face Liveness Detection
24%
Blood Flow Analysis
24%
Grey Model
24%
Deep Brain Stimulation Surgery
16%
Spectral Filter
16%
Elman Network
13%
Pruning Networks
13%
Recording Conditions
13%
Neural Spike Trains
12%
Intracortical Brain-machine Interface
12%
Subthalamic nucleus Deep Brain Stimulation (STN-DBS)
12%
GM(1,1)
12%
Pressure Filtration
12%
Population Vector
12%
Engineering
Feedforward
97%
Artificial Neural Network
24%
Receptive Field
24%
Graphene Oxide
24%
Inferior Frontal Gyrus
24%
Motor Imagery
24%
Learning Algorithm
24%
Robotics Application
24%
Fatigue Analysis
24%
Correction Learning
24%
Inertial Sensor
24%
Processing Parameter
24%
Brain-Computer Interface
24%
Experimental Result
23%
Prediction Error
22%
Fatigue Life
20%
Model Prediction
20%
Prediction Problem
19%
Hidden Neuron
16%
Sufficient Time
12%
Graphene
12%
Simulation Result
12%
Axis Accelerometer
12%
Motion Data
12%
Provide Protection
12%
Level Feature
12%
Fall Detection
12%
Sonication
12%
One Step
10%
Levenberg-Marquardt Algorithm
10%
Activation Function
9%
Decoding Performance
8%
Gamma Power
8%
Scale Feature
6%
Classification Accuracy
6%
Accurate Prediction
6%
Multiple Scale
6%
Multiscale
6%
Conditional Probability Density
6%
Cognition Function
6%
Neural Signal Processing
6%
Process System
6%
Transfer Learning
6%
State-of-the-Art Method
6%
Numerical Method
6%
Computer Science
Neural Network
100%
gray model
55%
Robotics Application
24%
Series Prediction
24%
Matching Algorithm
24%
Feedforward Neural Network
24%
Representation Learning
24%
Receptive Field
24%
Stereo Matching
24%
Computer Interface
24%
RGB-D Image
24%
Data Augmentation
24%
segmentation algorithm
24%
Liveness
24%
Spoofing Attack
24%
Experimental Result
20%
Prediction Phase
16%
Reaching Motion
12%
biometric authentication system
12%
Multi-Scale Local Binary Pattern
12%
Color Distribution
12%
Hopfield Neural Network
9%
Learning Phase
8%
Decoding Performance
8%
Model Prediction
8%
Discriminative Power
8%
Cognition Function
8%
Cognitive System
8%
Neural Signal Processing
8%
Intrinsic Property
8%
Learned Feature
8%
Prediction Error
7%
Single Variable
7%
Annotation
6%
Classification Accuracy
6%
Transfer Learning
6%
Feature Map
6%
Training Dataset
5%
