contentbased image classification using a neural network
designing and implementing a neural network library for handwriting detection, image analysis etc
Ngày tải lên :
28/04/2014, 10:10
... section explains how the training takes place, in a back ward propagation neural network. In a backward
propagation neural network, there are several layers, and each neuron in each layer is connected ... library.
3. Understanding Neural Networks
One fascinating thing about artificial neural networks is that, they are mainly inspired by the human brain. This doesn't
mean that Artificial Neural ... will be able to
Understand the basic theory behind neural networks (backward propagation neural networks in particular)
Understand how neural networks actually 'work'
Understand in more...
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Tài liệu A neural-network-based space-vector PWM controller for a three-level voltage-fed inverter induction motor drive doc
Ngày tải lên :
22/12/2013, 08:16
... Therefore,
it appears logical that a feedforward backpropagation-type
ANN which has high computational capability can implement
an SVM algorithm. Note that the ANN has inherent learning
capability that can ... linear
undermodulation region. A neural network has the advantage
of very fast implementation of an SVM algorithm, particularly
when a dedicated application-specific IC chip is used instead
of a ... bias time
and variable .The digital word corresponding to
as afunction of angle for both and states in all the phases
and in all the modes can be generated by simulation for training
a neural network. ...
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Báo cáo khoa học: "Discriminative Training of a Neural Network Statistical Parser" pdf
Ngày tải lên :
23/03/2014, 19:20
... the
fact that the DGSSN uses a large-vocabulary
tagger (Ratnaparkhi, 1996) as a preprocessing
stage may compensate for its smaller vocabu-
lary. Also, the main reason for using a smaller
vocabulary ... Empirical Methods in Natural
Language Processing, pages 133–142, Univ. of
Pennsylvania, PA.
Adwait Ratnaparkhi. 1999. Learning to parse
natural language with maximum entropy
models. Machine Learning, ... computationally tractable for
large datasets and a good approximation to the
theoretically optimal method. The parser which
uses this approach outperforms both a genera-
tive model and a discriminative...
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Báo cáo khoa học: "Document Classification Using a Finite Mixture Model" pdf
Ngày tải lên :
31/03/2014, 21:20
... Miyazaki Miyamae-ku Kawasaki, 216, Japan
Email: {lihang,yamanisi} @sbl.cl.nec.co.j p
Abstract
We propose a new method of classifying
documents into categories. We define for
each category a ... document classification. Guthrie
et. al. have devised a way suitable to documentation
classification. Suppose that there are two categories
cl ='tennis' and c2='soccer,' and ... Section 4. As a result,
FMM requires less data for parameter estimation
than WBM and thus can handle the data sparseness
problem quite well. Furthermore, it can economize
on the space necessary...
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vehicle signal analysis using artificial neural networks
Ngày tải lên :
28/04/2014, 10:02
... individual axle weights,
and ANNs for each stage. The ANN for the 1st stage calculates GVW by analyzing the dynamic strain
signal measured from the main girders and/or cross beams, and the 2nd ANN ... accuracy decreased for individual axle
weights [10].
The application of artificial neural networks (ANN) to the B-WIM was attempted in 2003 by
Gonzalez et al. for noise removal and calibration ... such as Geumdang Bridge since
appropriate strain readings could be acquired for obtaining information about number of axles, speed
and axle spacings of a vehicle. Also, appropriate strain readings...
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audio to visual speech synthesis using artificial neural networks
Ngày tải lên :
28/04/2014, 10:06
... acoustic waveform. An
artifical neural
network (ANN) was trained to map
the cepstral coefficients of an individual’s natural
speech to the control parameters of an animated
synthetic talking head. ... restricted amount of training data
avaliable from each speaker makes this data set a
hard test for the networks.
The training and generalization tests followed the
same general procedure as with ... be aligned perfectly with the natural
auditory speech utterances as they are being said.
This type of approach ideally allows for what is
called graceful degradation. That is, the acoustic
analysis...
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image classification using support vector
Ngày tải lên :
28/04/2014, 10:06
...
Artificial Neural Network (ANN) and Support Vector
Machine (SVM) applying for image classification.
3. A novel combination model (ANN_SVM)
apply for image classification
After the images ... extraction of image features is the fundamental
step for image classification. There are various types of
features for image classification s aim as follow: color
and shape features, statistical ... applying for image classification.
Firstly, we separate the image into many sub-images
based on the features of images. Each sub -image is
classified into the responsive class by an ANN. Finally,...
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large pattern recognition system using multi neural networks - codeproject
Ngày tải lên :
28/04/2014, 10:11
... bitmap.Dispose();
bitmap = null;
}
bitmap = new Bitmap(drawArea.Width, drawArea.Height);
drawArea.DrawToBitmap(bitmap, new Rectangle(0, 0, bitmap.Width, bitmap.Height));
drawBitmap =(Bitmap) ... significant decrease because bigger bad
written characters, many similar and confusable characters etc. Furthermore, assuming we can create a good enough
network which can recognize accurately ... outputlayer.Initialize();
network. Layers[5] = outputlayer;
network. TagetOutputs = Letters3;
network. UnknownOuput = '?';
}
Training a network
After creating a neural network using "Create...
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landscape image of regional tourism classification using neural network
Ngày tải lên :
28/04/2014, 10:06
... Ha Noi images and 254 Nha Trang
images (capture by digital camera). The test set has 82
images of Ha Long, Ha Noi, Nha Trang.
Because the input of Neural Network is vector data,
an image is ...
APPLY
FOR
IMAGE
CLASSIFICATION
Multi Artificial Neural Network (MANN), applying
for pattern or image classification with parameters
(m,L), has m Sub -Neural Network (SNN) and a ... calculation parameters.
Therefore, we use Neural Network to apply for
landscape image of regional tourism classification.
In this paper, we improve the Multi Artificial
Neural Network (MANN)...
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Estimation of Proper Strain Rate in the CRSC Test Using a Artificial Neural Networks
Ngày tải lên :
22/03/2013, 15:01
... results are used. 43 learning data are used for
training the ANN model, and the others are used for the comparison
Data Collection
Data Normalization
Parametric Studies
Training and Testing ANN ... the field data. In
particular, these differences are increase at the high strain rate range.
The reason is that ANN model has not a lot of database on the high
strain rate. To eliminate this ... fields. In this study, a back-propagation
neural network model for estimating of proper strain rate form soil
parameter is proposed. The back-propagation neural network program
adopted in the present...
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Báo cáo khoa học: "Fast Semantic Extraction Using a Novel Neural Network Architecture" docx
Ngày tải lên :
17/03/2014, 04:20
... is labeled for
each particular verb as so-called frames. Addition-
ally, semantic roles can also be labeled with one of
13 ARGM adjunct labels, such as ARGM-LOC or
ARGM-TMP for additional locational ... solves a multi-class prob-
lem using a one-vs-the-rest approach. The final sys-
tem, called ASSERT, gives state-of-the-art perfor-
mance and is also freely available at: http://
oak.colorado.edu/assert/. ... compli-
cated, consist of several stages and hand-
built features, and are too slow to be applied
as part of real applications that require such
semantic labels, partly because of their use
of a syntactic...
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a facial expression classification system integrating canny, principal component analysis and artificial neural network
Ngày tải lên :
28/04/2014, 10:06
...
Expression Classification Using Multi Artificial Neural
Network [11] in the same JAFFE database.
TABLE IV. COMPARATION CLASSIFICATION RATE OF METHODS
Method
Classification
Accuracy %
Rapid Facial ...
(Canny_PCA_ANN)
85.7%
This method (Canny_PCA_ANN) improved the
Classification Accuracy than Rapid Facial Expression
Classification Using Artificial Neural Networks [10] and
Facial Expression ... Artificial Neural
Network (ANN) apply for facial expression classification.
Canny and PCA apply for local facial feature extraction. A
facial image is separated to five local regions (left eye,...
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