AIMC Topic: Neural Networks, Computer

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Neural network model develops border ownership representation through visually guided learning.

Neurobiology of learning and memory
As Rubin's famous vase demonstrates, our visual perception tends to assign luminance contrast borders to one or other of the adjacent image regions. Experimental evidence for the neuronal coding of such border-ownership in the primate visual system h...

Deep learning architecture for air quality predictions.

Environmental science and pollution research international
With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and...

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

NeuroImage. Clinical
Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clin...

ANN Prediction of Metabolic Syndrome: a Complex Puzzle that will be Completed.

Journal of medical systems
The diagnosis of metabolic syndrome (MetS) has a leading role in the early prevention of chronic disease, such as cardiovascular disease, type 2 diabetes, cancers and chronic kidney disease. It would be very greatful that MetS diagnosis can be predic...

Learning the Relationship between the Primary Structure of HIV Envelope Glycoproteins and Neutralization Activity of Particular Antibodies by Using Artificial Neural Networks.

International journal of molecular sciences
The dependency between the primary structure of HIV envelope glycoproteins (ENV) and the neutralization data for given antibodies is very complicated and depends on a large number of factors, such as the binding affinity of a given antibody for a giv...

Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network.

Computational intelligence and neuroscience
Humans can easily classify different kinds of objects whereas it is quite difficult for computers. As a hot and difficult problem, objects classification has been receiving extensive interests with broad prospects. Inspired by neuroscience, deep lear...

Complete stability of delayed recurrent neural networks with Gaussian activation functions.

Neural networks : the official journal of the International Neural Network Society
This paper addresses the complete stability of delayed recurrent neural networks with Gaussian activation functions. By means of the geometrical properties of Gaussian function and algebraic properties of nonsingular M-matrix, some sufficient conditi...

Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis.

Environmental science and pollution research international
This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population and economic development ...

Detection of exudates in fundus photographs using deep neural networks and anatomical landmark detection fusion.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diabetic retinopathy is one of the leading disabling chronic diseases and one of the leading causes of preventable blindness in developed world. Early diagnosis of diabetic retinopathy enables timely treatment and in order t...