Machine Learning Classifiers Based Classification For IRIS Recognition

Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification

In this paper, we explore the effectiveness of bootstrapping supervised machine-learning polarity classifiers using the output of domain-independent rule-based classifiers. The benefit of this method is that no labeled training data are required. Still, this method allows to capture in-domain knowledge by training the supervised classifier on in-domain features, such as bag of words. We investi...

Machine learning based Visual Evoked Potential (VEP) Signals Recognition

Introduction: Visual evoked potentials contain certain diagnostic information which have proved to be of importance in the visual systems functional integrity. Due to substantial decrease of amplitude in extra macular stimulation in commonly used pattern VEPs, differentiating normal and abnormal signals can prove to be quite an obstacle. Due to developments of use of machine l...

Body Mass Index Classification based on Facial Features using Machine Learning Algorithms for utilizing in Telemedicine

Background and Objectives: Due to the impact of controlling BMI on life, BMI classification based on facial features can be used for developing Telemedicine systems and eliminating the limitations of measuring tools, especially for paralyzed people. So that physicians can help people online during the Covid-19 pandemic. Method: In this study, new features and some previous work features were e...

Iris recognition through machine learning techniques: A survey

Artificial Neural Networks based Classification Technique for Iris Recognition

Iris recognition is one of the challenging problems inhuman computer interaction. An automated iris recognition system requires an efficient method for classification of iris region in the face sequence, extraction of iris features, and construction of classification model. In recent years, Neural Networks (NN) has demonstrated excellent performance in a variety of classification problems. In t...