... Kanade
tk@cs.cmu.edu
http://www.cs.cmu.edu/˜tk
Abstract
We present a neural network -based face detection
system. A retinally connected neural network ex-
amines small windows of an image, and decides
whether ... tested this hy-
pothesis by using a separate neural network to ar-
bitrate among multiple detection networks. It was
found that the neural network -based arbitrationpro-
duces results comparable ... terms of detection
and false-positive rates.
1 Introduction
In this paper, we present a neural network -based al-
gorithmto detect frontalviewsof faces in gray-scale
images
1
. The algorithms...
... Face recognition/detection by probabilis-
tic decision -based neural network. IEEE Transactions on Neural Networks, Special Issue on
Artificial Neural Networks and Pattern Recognition, 8(1), January ... Zhang and John Fulcher. Face recognition using artificial neural
network group -based adaptive tolerance (GAT) trees. IEEE Transactions on Neural Networks,
7(3):555–567, 1996.
13
Figure 4: Left: ... CMU-
CS-92-115.
[
Rowley et al., 1998
]
Henry A. Rowley, Shumeet Baluja, and Takeo Kanade. Neural network-
based face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(1),
January...
... Artificial neural networks for feature extraction
and multivariate data projection. IEEE Trans. Neural Networks 6,
296 –317, 1995.
[2] B. Lerner, Toward a completely automatic neural network based
human ... 28,
Part B, Special issue on artificial neural networks, 544-552, 1998.
[3] B. Lerner, H. Guterman, Mayer Aladjem, A comparative study of
neural network based feature extraction paradigms. Pattern
Recognition. ... characters. However, the feature
extraction ability of MLP basedneural networks has not
been investigated properly. In this paper, a new MLP based
approach such as an auto-associator for feature extraction
from...
...
on neural network based classification. Then we summarize
the classification problems, occurring when dealing with
signatures, and propose solutions for them. In this paper a
complete neural ... 0.5 1.1
300x300 0.2 0.5 1.4 0.3 2.0 0.5 1.3
330x330 0.1 0.3 1.9 0.2 1.2 0.2 1.7
Neural Network -based Offline Handwritten Signature Verification System using Hu’s Moment Invariant Analysis ... and Advanced Technology (IJEAT)
ISSN: 2249 – 8958, Volume-1, Issue-1, October 2011
73
Neural Network -based Offline Handwritten
Signature Verification System using Hu’s Moment
Invariant Analysis...
... problem. In [8], neural
network inverse control techniques are applied for
trajectory tracking of a PD controlled rigid robot
manipulator.
In this study, a neural network based scheme is ...
from the desired position because of link deflections and
vibrations. In this study, a neural network based trajectory
planning method is applied to calculate modifications in the
command ... calculated by the
neural network. Simulations are performed to evaluate the
performance of the trajectory planning method and the
control procedure.
Index terms-flexible manipulator, neural network,...
... localized
neural networks.
3.2. Localized Neural Network Processing. The selected ANN’s
topology includes 40 hidden units in a single hidden
layer with feed-forward back-propagation neural network
architecture. ... [28].
3.2.1. Multiple Neural Networks Training and Selecting Local-
ized Neural Networks. The spectrogram and preprocessed
WVD of the two signals are used to train the multiple neural
networks. Fuzzy ... classifications based
on the algorithmic approach of the clustering techniques,
include the partitioning, hierarchical, graph-theoretic, and
objective function -based methods [3].
Localized neural processing...
... detector based on neural networks,” IEEE
Transactions on Pattern Analysis and Machine Intelligence, vol.
23, no. 1, pp. 42–53, 2001.
[10] H. A. Rowley, S. Baluja, and T. Kanade, Neural network-
based ... shows
the output value of the neural network. The neural network
is learned to pursue the desired value “1” for face and “–1”
for non-face.
3. Error Analysis of the Neural Network Caused
by Reduced-Precision ... accumulated error of the neural
network is obtained as shown in Ta bl e 11 .
4. Result and Discussion
4.1. FPGA Synthesis Results. The FPGA -based face detector
using the neural network and the...
... shorter time
slots.
The second question, related to the use of neural net-
works as the choice classifier, is based on the fact that neural
networks exhibit very good performance when compared to
other ... limited precision, this paper
focuses on.
The problem of implementing a neural- based sound
classifier in a hearing aid is that DSP -based hearing aids
have constraints in terms of computational capability ... processor the hearing aid is based on.
In this respect, the objective of this paper has been to
quantitatively analyzing these effects on the performance
of neural network -based sound classifiers in...
... side represents a kana-kanji con-
version process reinforced with a neural net-
work handler. The network is used by the
neural network handler and word associations
are done in parallel with ... to the neural network
handler through a homonym choice interface
and the corresponding node is activated.
The roles and the functions of main compo-
nents are described as follows.
* Neural ...
~~\ ',,
"t ~ 2"~J
~ ',, "-~
Figure 1: Kana-Kanji Conversion with a Neural Network
are too simple to disambiguate between possi-
ble previous selections for the same...
... The course describes how to design neural
networks with internal models. Model -based neural networks combine domain
knowledge with learning and adaptivity of neural networks.
Prerequisites: probability
Level: ... The course describes how to design neural
networks with internal models. Model -based neural networks combine domain
knowledge with learning and adaptivity of neural networks.
Prerequisites: probability ... emergence of a unified model -based pattern recognition method. We formulate
tracking as recognition of spatiotemporal patterns based on dynamic models, similar to
image recognition based on geometric models.
Classical...
... region -based fuzzy feature matching approach to content -based
image retrieval, Pattern Analysis and Machine Intelligence, IEEE Transactions on (2002)
1252-1267
10. Hoiem, D., et al.: Object -based ... classified into
responsive class using a Neural Network called Sub Neural Network (SNN) of
MANN. Lastly, we use MANN’s global frame (GF) consisting some Component
Neural Network (CNN) to compose the ... reliability coefficients. Our model links many Neural
Networks together, so we call it Multi Artificial Neural Network (MANN).
3 Multi Artificial Neural Network apply for image classification...