Computational and mathematical methods in medicine
Dec 14, 2016
. Similar to PET, absolute quantitative imaging is becoming available in commercial SPECT/CT devices. This study's goal was to assess quantitative accuracy of activity recovery as a function of image reconstruction parameters and count statistics in ...
In this paper, a new optimization approach is designed for convolutional neural network (CNN) which introduces explicit logical relations between filters in the convolutional layer. In a conventional CNN, the filters' weights in convolutional layers ...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dec 13, 2016
An assistive system for persons with vocal impairment due to dysarthria converts dysarthric speech to normal speech or text. Because of the articulatory deficits, dysarthric speech recognition needs a robust learning technique. Representation learnin...
The Fuzzy C Means (FCM) and Expectation Maximization (EM) algorithms are the most prevalent methods for automatic segmentation of MR brain images into three classes Gray Matter (GM), White Matter (WM) and Cerebrospinal Fluid (CSF). The major difficul...
BACKGROUND: The last decades witnessed an explosion of large-scale biological datasets whose analyses require the continuous development of innovative algorithms. Many of these high-dimensional datasets are related to large biological networks with f...
Computational intelligence and neuroscience
Dec 12, 2016
Locating the assignable causes by use of the abnormal patterns of control chart is a widely used technology for manufacturing quality control. If there are uncertainties about the occurrence degree of abnormal patterns, the diagnosis process is impos...
Neural networks : the official journal of the International Neural Network Society
Dec 10, 2016
Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performanc...
This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection su...
IEEE transactions on pattern analysis and machine intelligence
Dec 8, 2016
This paper investigates a new annotation technique that reduces significantly the amount of time to annotate training data for gesture recognition. Conventionally, the annotations comprise the start and end times, and the corresponding labels of gest...
The support vector machine (SVM) is a powerful classifier that has recently been implemented in a classification tree (SVMTreeG). This classifier partitioned the data by finding gaps in the data space. For large and complex datasets, there may be no ...
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