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Title: Neural Network-Based Face Detection
Page Link: Neural Network-Based Face Detection -
Posted By: computer science crazy
Created at: Friday 18th of September 2009 12:54:50 AM
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Neural Network-Based Face Detection
Abstract: We present a neural network-based upright frontal face detection system. A retinal connected neural network examines small windows of an image, and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We present a straightforward procedure for aligning positive face examples for training. To collect negative examples, we use a bootstrap algorithm, which adds false detections into the training set as training progr ....etc

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Title: face recognition using neural network seminars report pdf
Page Link: face recognition using neural network seminars report pdf -
Posted By:
Created at: Tuesday 16th of February 2016 05:54:38 PM
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Title: Artificial Neural Network Based Face Recognition System
Page Link: Artificial Neural Network Based Face Recognition System -
Posted By: nit_cal
Created at: Thursday 29th of October 2009 04:33:58 PM
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Abstract
Identify some unique feature in the face image of a person, and then extract that Feature and compare. The system Extract eye from the face image and the extracted Image is given to input layer of artificial neural network. After three levels of processing, this network will generate a string which will be compared to the string earlier stored in the database for that face image. If the generated string of the current image already exists in the database, then it can be concluded that the image data is already enter ....etc

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Title: Face recognition using laplaction face at java
Page Link: Face recognition using laplaction face at java -
Posted By: project topics
Created at: Monday 02nd of May 2011 01:33:03 PM
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Face recognition using laplaction face at java

The face recognition is a fairly controversial subject right now. A system such as this can recognize and track dangerous criminals and terrorists in a crowd, but some contend that it is an extreme invasion of privacy. The proponents of large-scale face recognition feel that it is a necessary evil to make our country safer. It could benefit the visually impaired and allow them to interact more easily with the environment. Also, a computer vision-based authentication system could be pu ....etc

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Title: Face Detection Through Neural Analysis
Page Link: Face Detection Through Neural Analysis -
Posted By: seminar project explorer
Created at: Tuesday 15th of March 2011 12:10:47 AM
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Face Detection Through Neural Analysis
Akhil G S, Gibu George
S4 Mechanical Engineering,
Muslim Association College Of Engineering, Venjaramoodu



Abstract
The aim of this paper is to implement an effective system to locate upright frontal faces on monochromatic images
with use of a neural network-based classifier. In this paper, A new approach to reduce the computation time taken
by fast neural nets for the searching process is presented. The principle of ....etc

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Title: FACE RECOGNITION USING Neural Network
Page Link: FACE RECOGNITION USING Neural Network -
Posted By: SHARMILAA
Created at: Tuesday 16th of February 2010 03:13:13 PM
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Title: Face Detection in images Neural networks Support Vector Machines
Page Link: Face Detection in images Neural networks Support Vector Machines -
Posted By: computer science technology
Created at: Wednesday 27th of January 2010 02:10:21 AM
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Face Detection in images : Neural networks & Support Vector Machines
ABSTRACT
Over the years, one of the many problems being dealt with by the computer-vision community is that of face detection and recognition in images. The applications of such a system are numerous, from automated security systems, census, intelligence information etc. In this report, we present our experience with two of the most successful techniques present today (,) and extensions of this work into other interesting applicati ....etc

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Title: FACE RECOGNITION USING Neural Network
Page Link: FACE RECOGNITION USING Neural Network -
Posted By: computer science crazy
Created at: Sunday 22nd of February 2009 01:11:21 AM
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Faces represent complex, multidimensional, meaningful visual stimuli
and developing a computational model for face recognition is difficult
. We present a hybrid neural network solution which compares
favorably with other methods. The system combines local image sampling,
a self-organizing map neural network, and a convolutional neural
network. The self-organizing map provides a quantization of the image
samples into a topological space where inputs that are nearby in the
original space are also nearby in the output space, thereby pr ....etc

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Title: Rules of Designing Routing Metrics for Greedy Face and Combined Greedy-Face Routing
Page Link: Rules of Designing Routing Metrics for Greedy Face and Combined Greedy-Face Routing -
Posted By: project report helper
Created at: Friday 29th of October 2010 07:00:50 PM
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Rules of Designing Routing Metrics for Greedy,
Face, and Combined Greedy-Face Routing


Yujun Li, Yaling Yang, and Xianliang Lu




Abstract—


Different geographic routing protocols have different requirements on routing metric designs to ensure proper operation.
Combining a wrong type of routing metrics with a geographic routing protocol may produce unexpected results, such as geographic
routing loops and unreachable nodes. In this paper, we propose a novel routing algebra system to investigate t ....etc

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Title: Neural Network-Based Face Detection
Page Link: Neural Network-Based Face Detection -
Posted By: electronics seminars
Created at: Wednesday 13th of January 2010 10:26:38 AM
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Neural Network-Based Face Detection

Abstract: We present a neural network-based upright frontal face detection system. A retinal connected neural network examines small windows of an image, and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We present a straightforward procedure for aligning positive face examples for training. To collect negative examples, we use a bootstrap algorithm, which adds false detections into the training set as training pr ....etc

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