All models of evolution of human behaviour depend on the correct identification and interpretation of bone surface modifications (BSM) on archaeofaunal assemblages. Crucial evolutionary features, such as the origin of stone tool use, meat-eating, foo...
Medical datasets are often predominately composed of "normal" examples with only a small percentage of "abnormal" ones and how to correctly recognize the abnormal examples is very meaningful. However, conventional classification learning methods try ...
Computational intelligence and neuroscience
Apr 10, 2018
This work considers the problem of utilizing electroencephalographic signals for use in systems designed for monitoring and enhancing the performance of aircraft pilots. Systems with such capabilities are generally referred to as cognitive cockpits. ...
Statistical methods in medical research
Apr 9, 2018
Extreme learning machines have gained a lot of attention by the machine learning community because of its interesting properties and computational advantages. With the increase in collection of information nowadays, many sources of data have missing ...
IEEE transactions on bio-medical engineering
Apr 9, 2018
Brain-wide and genome-wide association (BW-GWA) study is presented in this paper to identify the associations between the brain imaging phenotypes (i.e., regional volumetric measures) and the genetic variants [i.e., single nucleotide polymorphism (SN...
IEEE transactions on neural networks and learning systems
Apr 9, 2018
The deep convolutional neural network (DCNN) is a class of machine learning algorithms based on feed-forward artificial neural network and is widely used for image processing applications. Implementation of DCNN in real-world problems needs high comp...
BACKGROUND: Various technologies have been developed to improve hand hygiene (HH) compliance in inpatient settings; however, little is known about the feasibility of machine learning technology for this purpose in outpatient clinics.
Neural networks : the official journal of the International Neural Network Society
Apr 9, 2018
In this study, we introduce a novel category of double fuzzy clustering-driven context neural networks (DFCCNNs). The study is focused on the development of advanced design methodologies for redesigning the structure of conventional fuzzy clustering-...
RNA 5-methylcytosine (mC) is an important post-transcriptional modification that plays an indispensable role in biological processes. The accurate identification of mC sites from primary RNA sequences is especially useful for deeply understanding the...
Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version na...
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