Cortical networks are complex systems of a great many interconnected neurons that operate from collective dynamical states. To understand how cortical neural networks function, it is important to identify their common dynamical operating states from ...
Neural networks : the official journal of the International Neural Network Society
Jul 10, 2020
In this study, we consider the fixed-time synchronization problem for stochastic memristor-based neural networks (MNNs) via two different controllers. First, a new stochastic differential equation is established using differential inclusions and set-...
Neural networks : the official journal of the International Neural Network Society
Jul 6, 2020
In this paper, the protocol-based remote state estimation problem is considered for a kind of delayed artificial neural networks. The random time-varying delays fall into certain intervals with known probability distributions. For the sake of reducin...
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Jul 5, 2020
Responders need tools to rapidly detect and identify airborne alpha radioactivity during consequence management scenarios. Traditional continuous air monitoring systems used for this purpose compute the net counts in various energy windows to determi...
OBJECTIVES: High throughput pre-treatment imaging features may predict radiation treatment outcome and guide individualized treatment in radiotherapy (RT). Given relatively small patient sample (as compared with high dimensional imaging features), id...
This paper presents a new deep regression model, which we call DeepDistance, for cell detection in images acquired with inverted microscopy. This model considers cell detection as a task of finding most probable locations that suggest cell centers in...
Neural networks : the official journal of the International Neural Network Society
May 4, 2020
As a major step forward in machine learning, generative adversarial networks (GANs) employ the Wasserstein distance as a metric between the generative distribution and target data distribution, and thus can be viewed as optimal transport (OT) problem...
An efficient method for identifying subjects at high risk of an intracranial aneurysm (IA) is warranted to provide adequate radiological screening guidelines and effectively allocate medical resources. We developed a model for pre-diagnosis IA predic...
BACKGROUND: Generally, brain-computer interfaces (BCIs) require calibration before usage to ensure efficient performance. Therefore, each BCI user has to attend a certain number of calibration sessions to be able to use the system. However, such cali...
Deep learning is a class of machine learning algorithms that are popular for building risk prediction models. When observations are censored, the outcomes are only partially observed and standard deep learning algorithms cannot be directly applied. W...
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