Search Results - (( java adaptation optimization algorithm ) OR ( pattern extraction path algorithm ))
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1
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
2
Feature extraction: hand shape, hand position and hand trajectory path
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Book Chapter -
3
Animal voice recognition for identification (ID) detection system
Published 2011“…While the voice pattern classification will be done by using DTW algorithm. …”
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Conference or Workshop Item -
4
Dog voice identification (ID) for detection system
Published 2012“…While the voice pattern classification will be done by using DTW algorithm. …”
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5
NN with DTW-FF Coefficients and Pitch Feature for Speaker Recognition
Published 2006“…This paper proposes a new method to extract speech features in a warping path using dynamic programming (DP). …”
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Article -
6
Local DTW coefficients and pitch feature for back-propagation NN digits recognition
Published 2006“…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
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Conference or Workshop Item -
7
Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition
Published 2006“…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
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8
Advances in materials informatics: A review
Published 2024“…Conventional ML models are simple and interpretable, relying on statistical techniques and algorithms to learn patterns and make predictions with limited data. …”
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Article -
9
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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10
A hybrid environment control system combining EMG and SSVEP signal based on brain-computer interface technology
Published 2021“…The feature in terms of the common spatial pattern (CSP) has been extracted from four classes of SSVEP response, and extracted feature has been classified using K-nearest neighbors (k-NN) based classification algorithm. …”
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