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Segmented dynamic time warping based signal pattern classification
Jae Yeol Hong
, Seung Hwan Park
,
Jun Geol Baek
*
*
Corresponding author for this work
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
12
Citations (Scopus)
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Dive into the research topics of 'Segmented dynamic time warping based signal pattern classification'. Together they form a unique fingerprint.
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Keyphrases
Pattern Classification
100%
Dynamic Time Warping
100%
Signal Pattern
100%
Process Signal
75%
Fabrication Methods
50%
Unit Process
50%
Classification Algorithms
50%
Semiconductor Manufacturing Process
50%
Semiconductors
25%
Classification Performance
25%
Manufacturing Firms
25%
Time Series Data
25%
Random Sample Consensus (RANSAC)
25%
Semiconductor Process
25%
Manufacturing Systems
25%
Process Monitoring
25%
Sensor Type
25%
Fault Detection
25%
Packaging Process
25%
Trace Data
25%
Signal Classification
25%
Process Quality
25%
Process Yield
25%
Signal Data
25%
Fault Classification
25%
Maximal Overlap Discrete Wavelet Transform (MODWT)
25%
Process Equipment
25%
Data-driven Algorithm
25%
Time Series Characteristics
25%
Engineering
Semiconductor Manufacturing
100%
Process Unit
66%
Manufacturing Process
66%
Classification Algorithm
66%
Sensor Type
33%
Gas Fuel Manufacture
33%
Process Monitoring
33%
Classification Performance
33%
Manufacturing Company
33%
Data Series
33%
Random Sample
33%
Signal Data
33%
Process Yield
33%
Process Equipment
33%
Computer Science
Pattern Classification
100%
Dynamic Time Warping
100%
Classification Algorithm
50%
Classification Performance
25%
Wavelet Transforms
25%
Process Monitoring
25%
Time Series Data
25%
Fault detection
25%
Chemical Engineering
Process Monitoring
100%