Journal ArticleDOI
Probabilistic neural networks
TLDR
A probabilistic neural network that can compute nonlinear decision boundaries which approach the Bayes optimal is formed, and a fourlayer neural network of the type proposed can map any input pattern to any number of classifications.About:
This article is published in Neural Networks.The article was published on 1990-01-01. It has received 3772 citations till now. The article focuses on the topics: Probabilistic neural network & Activation function.read more
Citations
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Journal ArticleDOI
Identification, Segmentation, and Image Property Study of Acute Infarcts in Diffusion-Weighted Images by Using a Probabilistic Neural Network and Adaptive Gaussian Mixture Model
TL;DR: The method aids the clinician in reducing the time needed to localize and segment the acute brain infarcts and can be enhanced further by implementing the algorithm in VC++ and using fast algorithms for selection of Gaussian mixture model parameters.
Proceedings ArticleDOI
EIR — Efficient computer aided diagnosis framework for gastrointestinal endoscopies
Michael Riegler,Konstantin Pogorelov,Pål Halvorsen,Thomas de Lange,Carsten Griwodz,Peter T. Schmidt,Sigrun Losada Eskeland,Dag Johansen +7 more
TL;DR: A multimedia system to tackle automatic analysis of videos from the human gastrointestinal (GI) tract that combines filters using machine learning, image recognition and extraction of global and local image features, built in a modular way, so that it can be extended.
Journal ArticleDOI
A practical overview of neural networks
Laura I. Burke,James P. Ignizio +1 more
TL;DR: The myths and misconceptions that have surrounded neural networks in recent years are overviews, and alternatives or variants to backpropagation are considered, which overcome some of its real limitations.
Journal ArticleDOI
Can machine learning approaches predict corporate bankruptcy? Evidence from a qualitative experimental design
Salim Lahmiri,Stelios Bekiros +1 more
TL;DR: An empirical study to assess the effectiveness of various machine learning topologies trained with big data approaches and qualitative, rather than quantitative, information as input variables generates outperforming results compared to traditional methods for bankruptcy forecasting and risk measurement.
Journal ArticleDOI
Prediction of flow pattern of gas-liquid flow through circular microchannel using probabilistic neural network
Seim Timung,Tapas Kumar Mandal +1 more
TL;DR: Two separate PNN models has been developed to predict the flow patterns of gas-liquid flow through different channel diameter, one for diameter ranging from 0.53mm to 0.22mm and another for 0.100mm-0.05mm, both of which have been found to be in good agreement.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Journal ArticleDOI
On Estimation of a Probability Density Function and Mode
TL;DR: In this paper, the problem of the estimation of a probability density function and of determining the mode of the probability function is discussed. Only estimates which are consistent and asymptotically normal are constructed.
Book
Introduction to the Theory of Statistics
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
Journal ArticleDOI
Introduction to the Theory of Statistics.
Jacob Wolfowitz,A. M. Mood +1 more
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
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