Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other cl...

Breast cancer classification using deep belief networks

Over the last decade, the ever increasing world-wide demand for early detection of breast cancer at many screening sites and hospitals has resulted in the need of new research avenues. According to theWorld Health Organization (WHO), an early detection of cancer greatly increases the chances of taking the right decision on a successful treatment plan. The Computer-Aided Diagnosis (CAD) systems ...

Sparse Feature Learning for Deep Belief Networks

Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the raw input. Many unsupervised methods are based on reconstructing the input from the representation, while constraining the representation to have certain desirable properties (e.g. low dimension, sparsity, etc). Others a...

Subtractive Fuzzy Classifier Based Driver Distraction Levels Classification Using EEG

[Purpose] In earlier studies of driver distraction, researchers classified distraction into two levels (not distracted, and distracted). This study classified four levels of distraction (neutral, low, medium, high). [Subjects and Methods] Fifty Asian subjects (n=50, 43 males, 7 females), age range 20-35 years, who were free from any disease, participated in this study. Wireless EEG signals were...

[Article] EEG Based Eye State Classification using Deep Belief Network and Stacked AutoEncoder