Environmental science and pollution research international
Nov 19, 2019
Contamination source identification (CSI) is significant for water quality security and social stability when a contamination intrusion event occurs in water distribution systems (WDSs). However, in research, this is an extremely challenging task for...
Artificial intelligence (AI) is the development of computer systems that are able to perform tasks that normally require human intelligence. Advances in AI software and hardware, especially deep learning algorithms and the graphics processing units (...
OBJECTIVE: Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurobehavioral disorders. Studies have tried to find the neural correlations of ADHD with electroencephalography (EEG). Due to the heterogeneity in the ADHD popu...
Neural networks : the official journal of the International Neural Network Society
Nov 18, 2019
Image generation is a long-standing problem in the machine learning and computer vision areas. In order to generate images with high diversity, we propose a novel model called generative adversarial networks with mixture of t-distributions noise (tGA...
Deep Neural Network (DNN), as a deep architectures, has shown excellent performance in classification tasks. However, when the data has different distributions or contains some latent non-observed factors, it is difficult for DNN to train a single mo...
OBJECTIVES: The aim of the current study was to evaluate the detection and diagnosis of three types of odontogenic cystic lesions (OCLs)-odontogenic keratocysts, dentigerous cysts, and periapical cysts-using dental panoramic radiography and cone beam...
BACKGROUND: Rapid identification of new essential genes is necessary to understand biological mechanisms and identify potential targets for antimicrobial drugs. Many computational methods have been proposed.
The method of 3D fluorescence spectroscopy combined with convolutional neural network (CNN) was developed to identify the counterfeit sesame oil. AlexNet, a pre-trained CNN architecture, was transferred to extract spectral characteristics. Then these...
BACKGROUND AND AIMS: The aim of our study was to develop and evaluate a deep learning algorithm for the automated detection of small-bowel ulcers in Crohn's disease (CD) on capsule endoscopy (CE) images of individual patients.
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears to be a promising alternative for scar assessment in patients with atrial fibrillation (AF). Automating the quantification and analysis of atrial scars can be challenging due to...
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