SEGMENTATION WITH NEURAL NETWORK B.Prasanna Rahul Radhakrishnan Valliammai Engineering College Valliammai Engineering College prakrish_2001@yahoo.com krish_rahul_1812@yahoo.com Abstract: Our paper work is on Segmentation by Neural networks. Neural networks computation offers a wide range of different algorithms for both unsupervised clustering (UC) and supervised classification (SC). In this paper we approached an algorithmic method that aims to
Premium Neural network Brain Magnetic resonance imaging
H.O.D. Electrical Engg. Dept. APPLICATION OF ARTIFICIAL NEURAL NETWORKS IN VOLTAGE AND REACTIVE POWER CONTROL Abstract The aim of this seminar is to introduce a new technique to control the voltage and reactive power in power systems based on Artificial Neural Network (ANN). Feed-forward ANN with Back Propagation training algorithm is used and the training data is obtained by solving several abnormal conditions
Premium Neural network Artificial neural network Artificial intelligence
Mathematical Handwriting Recognition with a Neural Network and Calculation Author: Tyler Sondag Date: 4/22/07 For Dr. Pokorny ’s CSI 490 Course Abstract The goal of this project was to create a software system that recognizes handwritten mathematical expressions and computes the answer. No special syntax or formatting was to be required for these expressions‚ since a major goal of this system was for users to be able to use the system without having to learn anything new. Support was desired for
Premium Neural network Mathematics Output
we want to create group that have maximum similarity among members within each group… 5. Which of the following is the reason why neural networks have been applied in business classification problems? Able to learn the data‚ able to learn the models ’ nonparametric nature‚ its ability to generalize‚ All of the above 6. The main processing elements of a neural network are individual neurons 7. A software suite is created when several software products are integrated into system 8. One dose not
Premium Data mining Artificial neural network Neural network
ARTIFICIAL NEURAL NETWORK: USE IN MANAGEMENT Neuron Transfer Function: The transfer function of a neuron is chosen to have a number of properties which either enhance or simplify the network containing the neuron. Crucially‚ for instance‚ any multilayer perceptron using a linear transfer function has an equivalent single-layer network; a non-linear function is therefore necessary to gain the advantages of a multi-layer network. Types of neuron transfer function • Pure Linear Transfer Function
Premium Brain Machine learning Neuron
Artificial Neural Networks in Real-Life Applications Juan R. Rabuñal University of A Coruña‚ Spain Julián Dorado University of A Coruña‚ Spain IDEA GROUP PUBLISHING Hershey • London • Melbourne • Singapore TEAM LinG Acquisitions Editor: Development Editor: Senior Managing Editor: Managing Editor: Copy Editor: Typesetter: Cover Design: Printed at: Michelle Potter Kristin Roth Amanda Appicello Jennifer Neidig Amanda O’Brien Jennifer Neidig Lisa Tosheff Yurchak Printing Inc. Published
Premium Neural network Artificial neural network Neuron
Using an Artificial Neural Network Jason R. Bowling‚ Priscilla Hope‚ Kathy J. Liszka The University of Akron Akron‚ Ohio 44325-4003 {bowling‚ ph11‚ liszka}@uakron.edu Abstract We propose a method for identifying image spam by training an artificial neural network. A detailed process for preprocessing spam image files is given‚ followed by a description on how to train an artificial neural network to distinguish between ham and spam. Finally‚ we exercise the trained network by testing it against
Premium Neural network Artificial neural network Artificial intelligence
ARTIFICIAL NUERAL NETWORKS IN ACCOUNTING Sri Lankan Gold Price Forecasting - Using Artificial Neural Networks (ANN) Abstract According to Dr Kennedy D. Gunawardene in 2009 The Artificial Neural Network is a collection of simple processors connected together and Each processor can only perform a very straight forward mathematical task‚ but large network of them has much greater capabilities and can do many things which one of its own can’t. The aim of this study is to find a model for forecasting
Premium Artificial neural network Neural network Artificial intelligence
process of attempting to identify instances of network attacks by comparing current activity against the expected actions of an intruder. Most current approaches to misuse detection involve the use of rule-based expert systems to identify indications of known attacks. However‚ these techniques are less successful in identifying attacks which vary from expected patterns. Artificial neural networks provide the potential to identify and classify network activity based on limited‚ incomplete‚ and nonlinear
Premium Artificial intelligence Artificial neural network Expert system
HIGH-VOLTAGE NEURAL STIMULATOR COMBINED WITH A LOW-VOLTAGE RECORDER Ulrich Bihr‚ Jens Anders‚ Joachim Becker and Maurits Ortmanns Institute of Microelectronics‚ University of Ulm‚ Ulm‚ Germany Ulrich.Bihr@uni-ulm.de Abstract: This paper presents a high-voltage (HV) neural stimulator combined with a low-voltage (LV) neural recorder. In many bidirectional neural implementations with a high voltage compliance for the stimulation is it not possible to have a high density due to the high power
Premium Voltage Neuroscience Neural network