Neural Network-Based Face Detection


Introduction
In this paper, we present a neural network-based algorithm to detect upright, frontal views of faces
in gray-scale images1. The algorithm works by applying one or more neural networks directly to
portions of the input image, and arbitrating their results. Each network is trained to output the
presence or absence of a face. The algorithms and training methods are designed to be general,
with little customization for faces.
Many ....etc

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i m lukng for papers on low cost ,cheap eye gaze techniques without neural network and artificial intelligence after 2010 from acm,IEE or elsevier,springer etc
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to get information about the topic biological early brain cancer detection using artificial neural network related topic refer the page link bellow

http://seminarsprojects.net/Thread-an-improved-implementation-of-brain-tumor-detection-using-segmentation ....etc

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matlab code for breast cancer detection using neural network

Abstract

Breast cancer is an uncontrolled growth of breast cells. Cell in the body get divide, grow and die every day. This division and growth of cell is most of the in orderly manner but when their growth is out of control. The uncontrolled growth of cell forms the lump which is called as tumor. A tumor generally of two types benign (not dangerous) or malignant (dangerous to health). The malignant tumor which develops in breast is called as breast cancer. In this paper we use back ....etc

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ABSTRACT

In this paper a multilayer feedforward neural network based approach for vehicle detection is proposed. The main idea is to use such network to perform both feature extraction and classification. This simplicity enables real time applications. In order to achieve such capabilities, the network is trained by a new algorithm, proposed in this paper, named minimization of inter-class interference (MCI). Such algorithm aims to create a hidden space (i.e. feature space) where the patterns have a desirable statistical distribution. Regardin ....etc

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Hamming s classifier description
This project describes the properties, applications, and creation process of the Hamming Neural Network, working as the signals classifier.
You may notice that the model of network described in this project may be a little different than one described in a professional literature. That s because we created our network to implement it in the Matlab environment. Nevertheless, the network works correctly.
What kind of signals does the Hamming Network process?
Although the network works in an analog way, it p ....etc

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To get full information or details of project report on brain tumor detection using neural network please have a look on the pages

http://seminarsprojects.net/Thread-biological-early-brain-cancer-detection-using-artificial-neural-network-ppt

http://seminarsprojects.net/Thread-an-improved-implementation-of-brain-tumor-detection-using-segmentation

if you again feel trouble on project report on brain tumor detection using neural network please reply in that page and ask specific fields in project report on brain tumor detection using neural net ....etc

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To get full information or details of handwritten english character recognition using neural network please have a look on the pages

http://seminarsprojects.net/Thread-character-recognition-using-artificial-neural-network

http://seminarsprojects.net/Thread-character-recognition-in-a-hand-written-document-image

if you again feel trouble on handwritten english character recognition using neural network please reply in that page and ask specific fields ....etc

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about brain mri segmentation software tools, versions, instructions, methods used, advantages and disadvantages of specific methods ....etc

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ARTIFICIAL NEURAL NETWORK FOR MISUSE DETECTION


INTRODUCTION

INTRUSION DETECTION SYSTEMS (IDS)

Host-based IDS
Network-based IDS
Vulnerability-assessment IDS

COMPONENT OF Of IDS

An information source that provides a stream of event records
An analysis engine that identifies signs of intrusions
A response component that gene rates reactions based
on the outcome of the analysis engine.

Neural Network Intrusion Detection Systems

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