Support vector machine performance with optimal parameters identification in recognising asphyxiated infant cry

QR Code

Support vector machine performance with optimal parameters identification in recognising asphyxiated infant cry

Detection of asphyxia in infant at an early stage is crucial to reduce the rate of infant morbidity. The information regarding asphyxia can be extracted from infant cry signals using support vector machine (SVM) combined with effective feature selection methods such as principal component analysis (...

Full description

Bibliographic Details
Published in:	International Journal of Engineering and Technology(UAE)
Main Author:	Sahak R.; Mansor W.; Lee K.Y.; Zabidi A.
Format:	Article
Language:	English
Published:	Science Publishing Corporation Inc 2018
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082351063&doi=10.14419%2fijet.v7i3.15.17513&partnerID=40&md5=ac980edcc6bb458ee74ccc0856729923

Similar Items

Optimal features for classifying asphyxiated infant cry using support vector machine with RBF kernel
by: Sahak R.; Lee Y.K.; Mansor W.; Yassin A.I.M.; Zabidi A.
Published: (2011)

Orthogonal least square and optimized support vector machine with polynomial kernel for classifying asphyxiated infant cry
by: Sahak R.; Mansor W.; Lee Y.K.; Zabidi A.; Yassin A.I.M.
Published: (2011)

Detection of asphyxiated infant cry using support vector machine integrated with principal component analysis
by: Sahak R.; Lee Y.K.; Mansor W.; Yassin A.I.M.; Zabidi A.
Published: (2010)

Optimization of principal component analysis and support vector machine for the recognition of infant cry with asphyxia
by: Sahak R.; Mansor W.; Lee K.Y.; Zabidi A.; Yassin A.I.M.
Published: (2013)

Optimized Support Vector Machine for classifying infant cries with asphyxia using Orthogonal Least Square
by: Sahak R.; Lee Y.K.; Mansor W.; Yassin A.I.M.; Zabidi A.
Published: (2010)

Orthogonal least square based support vector machine for the classification of infant cry with asphyxia
by: Sahak R.; Mansor W.; Lee Y.K.; Mohd Yassin A.I.; Zabidi A.
Published: (2010)

Performance of Combined Support Vector Machine and Principal Component Analysis in recognizing infant cry with asphyxia
by: Sahak R.; Mansor W.; Lee Y.K.; Yassin A.I.M.; Zabidi A.
Published: (2010)

Binary particle swarm optimization and f-ratio for selection of features in the recognition of asphyxiated infant cry
by: Zabidi A.; Mansor W.; Khuan L.Y.; Yassin I.M.; Sahak R.
Published: (2011)

Choice for a support vector machine kernel function for recognizing asphyxia from infant cries
by: Sahak R.; Mansor W.; Khuan L.Y.; Yassin A.I.M.; Zabidi A.; Yasmin F.; Rahman A.
Published: (2009)

Particle swarm optimisation of mel-frequency cepstral coefficients computation for the classification of asphyxiated infant cry
by: Zabidi A.; Mansor W.; Lee Y.K.; Mohd Yassin A.I.; Sahak R.
Published: (2010)

Detection of asphyxia from infant cry by linear kernel support vector machine enhanced with features from orthogonal least square
by: Sahak R.; Lee Y.K.; Mansor W.; Zabidi A.; Yassin A.I.M.
Published: (2011)

The effect of F-ratio in the classification of asphyxiated infant cries using multilayer perceptron neural network
by: Zabidi A.; Mansor W.; Khuan L.Y.; Yassin I.M.; Sahak R.
Published: (2010)

Detection of asphyxia from infant cry using support vector machine and multilayer perceptron integrated with Orthogonal Least Square
by: Sahak R.; Mansor W.; Khuan L.Y.; Zabidi A.; Yassin A.I.M.
Published: (2012)

Three-dimensional particle swam optimisation of Mel Frequency Cepstrum Coefficient computation and multilayer perceptron neural network for classifying asphyxiated infant cry
by: Zabidi A.; Mansor W.; Khuan L.Y.; Yassin I.M.; Sahak R.
Published: (2011)

Binary particle swarm optimization for selection of features in the recognition of infants cries with asphyxia
by: Zabidi A.; Mansor W.; Lee Y.K.; Yassin I.M.; Sahak R.
Published: (2011)

Performance comparison between mutative and constriction PSO in optimizing MFCC for the classification of hypothyroid infant cry
by: Zabidi A.; Mansor W.; Lee Y.K.; Yassin I.M.; Sahak R.
Published: (2011)

Investigation of Mel Frequency Cepstrum Coefficients parameters for classification of infant cries with hypothyroidism using MLP classifier
by: Zabidi A.; Mansor W.; Khuan L.Y.; Yassin I.M.; Sahak R.
Published: (2010)

Classification of infant cries with asphyxia using multilayer perceptron neural network
by: Zabidi A.; Khuan L.Y.; Mansor W.; Yassin I.M.; Sahak R.
Published: (2010)

Classification of infant cries with hypothyroidism using multilayer perceptron neural network
by: Zabidi A.; Mansor W.; Khuan L.Y.; Yassin I.M.; Sahak R.
Published: (2009)

An orthogonal least square approach to select features of infant cry with asphyxia
by: Sahak R.; Mansor W.; Khuan L.Y.; Yassin A.I.M.; Zabidi A.
Published: (2010)

Discrete Mutative Particle Swarm Optimisation of MFCC computation for classifying hypothyroidal infant cry
by: Zabidi A.; Mansor W.; Khuan L.Y.; Yassin I.M.; Sahak R.
Published: (2010)

Optimization of MFCC parameters using Particle Swarm Optimization for diagnosis of infant hypothyroidism using Multi-Layer Perceptron
by: Zabidi A.; Khuan L.Y.; Mansor W.; Yassin I.M.; Sahak R.
Published: (2010)

Sequential minimal optimization algorithm with support vector machine for mosquito larvae identification
by: Yusoff M.; Jefri N.J.; Shahar M.K.
Published: (2017)

Binary particle swarm optimization for feature selection in detection of infants with hypothyroidism
by: Zabidi A.; Khuan L.Y.; Mansor W.; Yassin I.M.; Sahak R.
Published: (2011)

Support vector machine with theta-beta band power features generated from writing of dyslexic children
by: Mahmoodin Z.; Lee K.Y.; Mansor W.; Zainuddin A.Z.A.
Published: (2019)

Convolution Neural Network Performance in Recognising EEG Signals of Dyslexic Children
by: Mansor W.; Ahmad Zainuddin A.Z.; Mohd Hanafi M.F.
Published: (2022)

Kinect-based frontal view gait recognition using support vector machine
by: Sahak R.; Md Tahir N.; Yassin I.; Zaman F.H.H.K.
Published: (2018)

Differentiation of Agarwood oil quality using Support Vector Machine (SVM)
by: Jantan H.; Yassin I.M.; Zabidi A.; Ismail N.; Ali M.S.A.M.
Published: (2017)

AN OPTIMIZED SUPPORT VECTOR MACHINE WITH GENETIC ALGORITHM FOR IMBALANCED DATA CLASSIFICATION
by: Shamsudin H.; Yusof U.K.; Haijie Y.; Isa I.S.
Published: (2023)

Detection of infant hypothyroidism with mel frequency cepstrum analysis and multi-layer perceptron classification
by: Zabidi A.; Khuan L.Y.; Mansor W.; Yassin I.M.; Sahak R.
Published: (2010)

Classification of SERS-based Fish and Beef Gelatin using Support Vector Machine
by: Saharuddin K.D.; Mansor W.; Jaafar S.A.; Khan Z.I.; Mahmud A.R.
Published: (2024)

Daily River Flow Forecasting with Hybrid Support Vector Machine - Particle Swarm Optimization
by: Zaini N.; Malek M.A.; Yusoff M.; Mardi N.H.; Norhisham S.
Published: (2018)

Anomalous gait detection based on support vector machine
by: Manap H.H.; Tahir N.Md.; Yassin A.I.M.
Published: (2011)

Content Based-Image Retrieval Using Support Vector Machine
by: Shahrom S.I.; Mohamed N.; Kamarudin S.F.; Ghazali W.N.A.W.; Malek A.A.
Published: (2021)

Knots timber detection and classification with C-support vector machine
by: Redzuan F.I.M.; Yusoff M.
Published: (2019)

Weed classification using one class support vector machine
by: Shahbudin S.; Zamri M.; Kassim M.; Abdullah S.A.C.; Suliman S.I.
Published: (2017)

Exploring feature selection and support vector machine in text categorization
by: Abdul-Rahman S.; Mutalib S.; Khanafi N.A.; Ali A.M.
Published: (2013)

Classification of transient in power system using support vector machine
by: Harnzah N.; Anuwar F.H.; Zakaria Z.; Tahir N.Md.
Published: (2009)

A review of the application of support vector machines in landslide susceptibility mapping
by: Yusof M.K.T.M.; Rashid A.S.A.; Apandi N.M.; Khanan M.F.B.A.; Rahman M.Z.B.A.
Published: (2023)

Fault classification in smart distribution network using support vector machine
by: Chuan O.W.; Ab Aziz N.F.; Yasin Z.M.; Salim N.A.; Wahab N.A.
Published: (2020)