H.6. Pattern Recognition
Robust Iris Recognition in Unconstrained Environments

A. Noruzi; M. Mahlouji; A. Shahidinejad

Volume 7, Issue 4 , November 2019, , Pages 495-506

https://doi.org/10.22044/jadm.2019.7434.1884

Abstract
  A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by him/her. Iris recognition (IR) is known to be the most reliable and accurate biometric identification system. The iris recognition system (IRS) consists of an automatic segmentation ...  Read More

H.6. Pattern Recognition
2D Dimensionality Reduction Methods without Loss

S. Ahmadkhani; P. Adibi; A. ahmadkhani

Volume 7, Issue 1 , January 2019, , Pages 203-212

https://doi.org/10.22044/jadm.2017.5063.1610

Abstract
  In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application. In this framework, the benefits of dimensionality reduction were ...  Read More

H.6. Pattern Recognition
A Geometry Preserving Kernel over Riemannian Manifolds

Kh. Sadatnejad; S. Shiry Ghidari; M. Rahmati

Volume 6, Issue 2 , July 2018, , Pages 321-334

https://doi.org/10.22044/jadm.2017.1000

Abstract
  Abstract- Kernel trick and projection to tangent spaces are two choices for linearizing the data points lying on Riemannian manifolds. These approaches are used to provide the prerequisites for applying standard machine learning methods on Riemannian manifolds. Classical kernels implicitly project data ...  Read More

H.6. Pattern Recognition
Holistic Farsi handwritten word recognition using gradient features

Z. Imani; Z. Ahmadyfard; A. Zohrevand

Volume 4, Issue 1 , March 2016, , Pages 19-25

https://doi.org/10.5829/idosi.JAIDM.2016.04.01.03

Abstract
  In this paper we address the issue of recognizing Farsi handwritten words. Two types of gradient features are extracted from a sliding vertical stripe which sweeps across a word image. These are directional and intensity gradient features. The feature vector extracted from each stripe is then coded using ...  Read More

H.6. Pattern Recognition
Classification of ECG signals using Hermite functions and MLP neural networks

A. Ebrahimzadeh; M. Ahmadi; M. Safarnejad

Volume 4, Issue 1 , March 2016, , Pages 55-65

https://doi.org/10.5829/idosi.JAIDM.2016.04.01.07

Abstract
  Classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. This paper proposes a three module system for classification of electrocardiogram (ECG) beats. These modules are: denoising module, feature extraction module and a classification module. ...  Read More

H.6. Pattern Recognition
IRDDS: Instance reduction based on Distance-based decision surface

J. Hamidzadeh

Volume 3, Issue 2 , July 2015, , Pages 121-130

https://doi.org/10.5829/idosi.JAIDM.2015.03.02.01

Abstract
  In instance-based learning, a training set is given to a classifier for classifying new instances. In practice, not all information in the training set is useful for classifiers. Therefore, it is convenient to discard irrelevant instances from the training set. This process is known as instance reduction, ...  Read More