Comparison on three classification techniques for sex estimation from the bone length of Asian children below 19 years old: An analysis using different group of ages

2015 ◽  
Vol 247 ◽  
pp. 130.e1-130.e11 ◽  
Author(s):  
M.F. Darmawan ◽  
Suhaila M. Yusuf ◽  
M.R. Abdul Kadir ◽  
H. Haron
Keyword(s):  
Sex Estimation ◽  
Classification Techniques ◽  
Bone Length ◽  
Asian Children

Comparison of Two Classification Models for Sex Estimation Based on Bone Length of Hispanic Population

2021 ◽  
Author(s):  
Mohd. Faaizie Darmawan ◽  
Ferda Ernawan ◽  
Ahmad Firdaus Zainal Abidin ◽  
Fajar Agung Nugroho ◽  
Mohd Zamri Osman
Keyword(s):  
Sex Estimation ◽  
Hispanic Population ◽  
Classification Models ◽  
Bone Length

Age estimation based on bone length using 12 regression models of left hand X-ray images for Asian children below 19 years old

2015 ◽  
Vol 17 (2) ◽  
pp. 71-78 ◽  
Author(s):  
M.F. Darmawan ◽  
Suhaila M. Yusuf ◽  
M.R. Abdul Kadir ◽  
H. Haron
Keyword(s):  
Age Estimation ◽  
Regression Models ◽  
X Ray ◽  
Left Hand ◽  
Bone Length ◽  
Asian Children

Advancement of Criminal Profiling Classification Techniques Using a Multi-Method Scaling Framework

2012 ◽  
Author(s):  
Alasdair Matthew Goodwill ◽  
Skye Stephens ◽  
Sandra Oziel ◽  
Nicola Bowes
Keyword(s):  
Criminal Profiling ◽  
Classification Techniques

HYBRID CLASSIFICATION SCHEMES FOR HEART MURMUR DETECTION TO ASSIST PHONOCARDIOGRAM BASED SIGNAL ACQUISITION

2017 ◽  
Vol 13 (9) ◽  
pp. 6480-6488 ◽  
Author(s):  
A.D. Jeyarani ◽  
Reena Daphne ◽  
Solomon Roach
Keyword(s):  
Neural Network ◽  
Signal Acquisition ◽  
Heart Murmur ◽  
Classification Techniques ◽  
Classification Schemes ◽  
Neural Network Classification ◽  
Nonlinear Classification ◽  
Processing Step ◽  
System Characterization ◽  
Hybrid Classification

The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.

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