R. Sahak

发表

Optimal Features for Classifying Asphyxiated Infant Cry Using Support Vector Machine with RBF Kernel

Y. K. Lee, A. Yassin, R. Sahak, 2011 .

Detection of asphyxia from infant cry by linear kernel support vector machine enhanced with features from orthogonal least square

Y. K. Lee, A. Yassin, R. Sahak, 2011, 2011 IEEE International Conference on Computer Applications and Industrial Electronics (ICCAIE).

Orthogonal least square based support vector machine for the classification of infant cry with asphyxia

Y. K. Lee, A. I. Mohd Yassin, R. Sahak, 2010, 2010 3rd International Conference on Biomedical Engineering and Informatics.

Performance of Principal Component Analysis and Orthogonal Least Square on Optimized Feature Set in Classifying Asphyxiated Infant Cry Using Support Vector Machine

Khuan Y. Lee, R. Sahak, W. Mansor, 2018 .

Detection of infant hypothyroidism with mel frequency cepstrum analysis and multi-layer perceptron classification

Rohilah Sahak, Azlee Zabidi, Wahidah Mansor, 2010, 2010 6th International Colloquium on Signal Processing & its Applications.

Autism spectrum disorders gait identification using ground reaction forces

Rohilah Sahak, Nooritawati Md Tahir, Rozita Jailani, 2017 .

Design of Mobile Application for SME Business Sustainability During Post Covid-19

Muhammad Farhan Affendi bin Yunos, A. Mansor, R. Sahak, 2022, 2022 International Visualization, Informatics and Technology Conference (IVIT).

Machine Learning Facemask Detection Models for COVID-19

R. Sahak, A. A. Puzi, A. Zainuddin, 2022, 2022 IEEE International Conference on Semiconductor Electronics (ICSE).

Classification of Infant Cries with Asphyxia Using Multilayer Perceptron Neural Network

Rohilah Sahak, Azlee Zabidi, Wahidah Mansor, 2010, 2010 Second International Conference on Computer Engineering and Applications.

Human gait recognition using orthogonal least square as feature selection

N. Tahir, A. Yassin, R. Sahak, 2020 .

Classification of infant cries with hypothyroidism using Multilayer Perceptron neural network

Rohilah Sahak, Azlee Zabidi, Wahidah Mansor, 2009, 2009 IEEE International Conference on Signal and Image Processing Applications.

Mel-frequency cepstrum coefficient analysis of infant cry with hypothyroidism

Rohilah Sahak, Azlee Zabidi, Wahidah Mansor, 2009, 2009 5th International Colloquium on Signal Processing & Its Applications.

Parkinson's disease feature subset selection based on voice samples

N. M. Tahir, R. Sahak, Z. A. Bakar, 2012, 2012 International Symposium on Computer Applications and Industrial Electronics (ISCAIE).

Three-dimensional particle swam optimisation of Mel Frequency Cepstrum Coefficient computation and Multilayer Perceptron neural network for classifying asphyxiated infant cry

Rohilah Sahak, Azlee Zabidi, Wahidah Mansor, 2011, 2011 IEEE International Conference on Computer Applications and Industrial Electronics (ICCAIE).

Discrete Mutative Particle Swarm Optimisation of MFCC computation for classifying hypothyroidal infant cry

Rohilah Sahak, Azlee Zabidi, Wahidah Mansor, 2010, 2010 International Conference on Computer Applications and Industrial Electronics.

Performance of Combined Support Vector Machine and Principal Component Analysis in recognizing infant cry with asphyxia

A. Zabidi, R. Sahak, W. Mansor, 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

Human gait recognition based on frontal view using kinect features and orthogonal least square selection

Rohilah Sahak, Ahmad Ihsan Mohd Yassin, Nooritawati Md. Tahir, 2017, 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).

Optimization of locally linear embedded for frontal gait recognition using kinect

Rohilah Sahak, Ahmad Ihsan Mohd Yassin, Nooritawati Md. Tahir, 2017, 2017 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE).

Binary Particle Swarm Optimization for selection of features in the recognition of infants cries with asphyxia

Rohilah Sahak, Azlee Zabidi, Wahidah Mansor, 2011, 2011 IEEE 7th International Colloquium on Signal Processing and its Applications.

Optimized Support Vector Machine for classifying infant cries with asphyxia using Orthogonal Least Square

A. Zabidi, R. Sahak, W. Mansor, 2010, 2010 International Conference on Computer Applications and Industrial Electronics.

Optimization of MFCC parameters using Particle Swarm Optimization for diagnosis of infant hypothyroidism using Multi- Layer Perceptron

I. M. Yassin, A. Zabidi, R. Sahak, 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

The effect of F-ratio in the classification of asphyxiated infant cries using multilayer perceptron Neural Network

I. M. Yassin, A. Zabidi, R. Sahak, 2010, 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES).

Investigation of Mel Frequency Cepstrum Coefficients parameters for classification of infant cries with hypothyroidism using MLP classifier

Rohilah Sahak, Ahmad Ihsan Mohd Yassin, Azlee Zabidi, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

An investigation into infant cry and Apgar score using principle component analysis

Rohilah Sahak, Azlee Zabidi, Wahidah Mansor, 2009, 2009 5th International Colloquium on Signal Processing & Its Applications.

Human Gait Recognition Using Skeleton Joint Coordinates with Orthogonal Least Square and Locally Linear Embedded Techniques

Rohilah Sahak, Ahmad Ihsan Mohd Yassin, Nooritawati Md Tahir, 2019, International journal of simulation: systems, science & technology.

RECOGNITION OF HUMAN GAIT IN OBLIQUE AND FRONTAL VIEWS USING KINECT

Azlee Zabidi, Nooritawati Md Tahir, Ihsan Mohd Yassin, 2018 .

Object detection using depth information from Kinect sensor

A. Zabidi, R. Sahak, I. Yassin, 2015, 2015 IEEE 11th International Colloquium on Signal Processing & Its Applications (CSPA).

Support Vector Machine Performance with Optimal Parameters Identification in Recognising Asphyxiated Infant Cry

Azlee Zabidi, Wahidah Mansor, Khuan Y. Lee, 2018, International Journal of Engineering & Technology.