|
Paper Title |
Authors |
Conference |
Abstract |
|
|
Long Term Electrical Load Forecasting via a Neurofuzzy Model |
M. Nosrati Maralloo
A. R. Koushki
C. Lucas
A. Kalhor
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Long-term forecasting of load demand is necessary
for the correct operation of electric utilities. There is
an on-going attention toward putting new approaches
to the task. Recently, Neurofuzzy modeling has played
a successful role ... more
Long-term forecasting of load demand is necessary
for the correct operation of electric utilities. There is
an on-going attention toward putting new approaches
to the task. Recently, Neurofuzzy modeling has played
a successful role in various applications over
nonlinear time series prediction. This paper presents a
neurofuzzy model for long-term load forecasting. This
model is identified through Locally Linear Model Tree
(LoLiMoT) learning algorithm. The model is compared
to a multilayer perceptron and hierarchical hybrid
neural model (HHNM). The models are trained and
assessed on load data extracted from a North-
American electric utility. less
Long-term forecasting of load demand is necessary
for the correct operation of electric utilities. There is
an on-going attention toward putting new approaches
to the task. Recently, Neurofuzzy modeling has played
a successful role ... more |
خرید مقاله
|
|
Document image binarization by using texture-edge descriptor |
N. Armanfard
M. Valizadeh
M. Komeili
E. Kabir
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper we propose a new approach for text
region extraction in camera-captured document
images. Texture-Edge Descriptor, TED, is utilized for
text region extraction. TED is an 8-bit binary number
which its bits ... more
In this paper we propose a new approach for text
region extraction in camera-captured document
images. Texture-Edge Descriptor, TED, is utilized for
text region extraction. TED is an 8-bit binary number
which its bits are structural. This structural bits and
special text region characteristics in document images
make TED an appropriate descriptor for text region
extraction. Applying well-known water flow method to
the text regions extracted by TED, results in fast and
good quality document image binarization.
Experimental results demonstrate the effectiveness of
our method for text region extraction and document
image binarization. less
In this paper we propose a new approach for text
region extraction in camera-captured document
images. Texture-Edge Descriptor, TED, is utilized for
text region extraction. TED is an 8-bit binary number
which its bits ... more |
خرید مقاله
|
|
A Novel Hybrid Algorithm for Binarization of Badly Illuminated Document Images |
M. valizadeh
M. komeili
E. kabir
N. armanfard
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. ... more
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. Afterward a simple global
binarization algorithm binarizes the enhanced image.
The enhancement process is a novel method that uses a
separate transformation function to map the gray level
of each pixel into a new domain. For each pixel, the
transformation function is determined using its
neighboring pixels gray level. The proposed
binarization algorithm is robust for wide variety of
degraded document images. Evaluation over a set of
degraded document images illustrates the effectiveness
of our proposed binarization algorithm. less
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. ... more |
خرید مقاله
|
|
A Novel Hybrid Algorithm for Binarization of Badly Illuminated Document Images |
M. valizadeh
N. armanfard
M. komeili
E. kabir
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. ... more
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. Afterward a simple global
binarization algorithm binarizes the enhanced image.
The enhancement process is a novel method that uses a
separate transformation function to map the gray level
of each pixel into a new domain. For each pixel, the
transformation function is determined using its
neighboring pixels gray level. The proposed
binarization algorithm is robust for wide variety of
degraded document images. Evaluation over a set of
degraded document images illustrates the effectiveness
of our proposed binarization algorithm. less
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. ... more |
خرید مقاله
|
|
A Novel Hybrid Algorithm for Binarization of Badly Illuminated Document Images |
M. valizadeh
N. armanfard
M. komeili
E. kabir
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. ... more
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. Afterward a simple global
binarization algorithm binarizes the enhanced image.
The enhancement process is a novel method that uses a
separate transformation function to map the gray level
of each pixel into a new domain. For each pixel, the
transformation function is determined using its
neighboring pixels gray level. The proposed
binarization algorithm is robust for wide variety of
degraded document images. Evaluation over a set of
degraded document images illustrates the effectiveness
of our proposed binarization algorithm. less
In this paper, we present a novel hybrid algorithm
for binarization of badly illuminated document images.
This algorithm locally enhances the document image
and makes the gray levels of text and background
pixels separable. ... more |
خرید مقاله
|
|
An optimal fuzzy system for feature reliability measuring in particle filterbased object tracking |
M. Komeili
M. Valizadeh
N. Armanfard
E. Kabir
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, a fuzzy inference system by which
reliability of features can be measured is designed.
The reliability determines discriminative power of a
feature in separating target from background. We
focus our attention ... more
In this paper, a fuzzy inference system by which
reliability of features can be measured is designed.
The reliability determines discriminative power of a
feature in separating target from background. We
focus our attention on design of membership functions.
With a rational explanation on available information
over a particle filter-base tracking process, we infer a
coarse estimation of membership functions. It follows
with a fine-tuning stage by using genetic algorithm.
Color, edge, texture and TED are used in current work
but the extension to a wider number of features is
straightforward. less
In this paper, a fuzzy inference system by which
reliability of features can be measured is designed.
The reliability determines discriminative power of a
feature in separating target from background. We
focus our attention ... more |
خرید مقاله
|
|
Effective Hierarchical background modeling and foreground detection in surveillance systems |
N. Armanfard
M. Komeili
M. Valizadeh
E. Kabir
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Background modeling is one of the most important
parts of visual surveillance systems. Most background
models are pixel-based which extract detailed shape
of moving objects, but they are so sensitive to nonstationary
scenes. In ... more
Background modeling is one of the most important
parts of visual surveillance systems. Most background
models are pixel-based which extract detailed shape
of moving objects, but they are so sensitive to nonstationary
scenes. In many applications there is no
need to detect the detailed shape of moving objects.
So some researchers use block-based methods instead
of pixel-based which are more insensitive to local
movements. These two methods are complementary to
each other. We propose an efficient hierarchical
method by which the block level information is
utilized intelligently to improve the efficiency and
robustness of pixel level. Experimental results
demonstrate the effectiveness of the algorithm when
applied in different outdoor and indoor environments. less
Background modeling is one of the most important
parts of visual surveillance systems. Most background
models are pixel-based which extract detailed shape
of moving objects, but they are so sensitive to nonstationary
scenes. In ... more |
خرید مقاله
|
|
Improving EEG Signal Prediction via SSA and Channel Selection |
Bahareh Atoufi
Ali Zakerolhosseini
Caro Lucas
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Being able to predict the coming seizure can
impressively improve the quality of the patients' lives
since they can be warned to avoid doing risky activities
via a prediction system. Here, a locally ... more
Being able to predict the coming seizure can
impressively improve the quality of the patients' lives
since they can be warned to avoid doing risky activities
via a prediction system. Here, a locally linear neuro
fuzzy model is used to predict the EEG time series.
Subsequently, this model is utilized in accompany with
Singular Spectrum Analysis for prediction. Afterward,
an information theoretic criterion is used to select a
reliable subset of input variables which contain more
information about the target signal. Comparison of
three mentioned methods on one hand shows that SSA
enables our prediction model to extract the main
patterns of the EEG signal and highly improves the
prediction accuracy. On the other hand, applying the
method of channel selection to the model yields more
accurate prediction. It is shown that fusion of some
certain signals provides more information about the
target and considerably improves the prediction
ability. less
Being able to predict the coming seizure can
impressively improve the quality of the patients' lives
since they can be warned to avoid doing risky activities
via a prediction system. Here, a locally ... more |
خرید مقاله
|
|
Video Summarization Using Genetic Algorithm and Information Theory |
Zeinab Zeinalpour Tabrizi
Behrouz Minaei Bidgoli
Mahmud Fathi
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Video processing techniques based on pattern
recognition methods and machine vision is one of the
interesting research fields which attract many
researchers. In this paper, we proposed a novel
method for video summarization using ... more
Video processing techniques based on pattern
recognition methods and machine vision is one of the
interesting research fields which attract many
researchers. In this paper, we proposed a novel
method for video summarization using genetic
algorithm based on information theory. Our method
relies on the mutual information for video
summarization. The information theory measure
provides us with better results because it extracts the
inter-frame information. We present that it is a suitable
factor for summarizing video, which maintains its
integrity. less
Video processing techniques based on pattern
recognition methods and machine vision is one of the
interesting research fields which attract many
researchers. In this paper, we proposed a novel
method for video summarization using ... more |
خرید مقاله
|
|
Sparse Modeling of Heart Sounds and Murmurs based on Orthogonal Matching Pursuit |
Sepideh Jabbari
Hassan Ghassemian
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, we address the Heart Sound signal
modeling problem. The approach taken is based on
sparse and redundant representations on an
overcomplete dictionary. We apply matching pursuit
(MP) and orthogonal matching pursuit ... more
In this paper, we address the Heart Sound signal
modeling problem. The approach taken is based on
sparse and redundant representations on an
overcomplete dictionary. We apply matching pursuit
(MP) and orthogonal matching pursuit (OMP) on two
sets of normal and pathological phonocardiograms
(PCGs). The dictionary includes classical Gabor
wavelets or time-frequency atoms which are the
product of a sinusoid and a Gaussian window function.
The normalized root-mean-square error (NRMSE) was
computed between the original and the reconstructed
signals. The results show that the OMP method is very
suitable to the transient and complex properties of the
PCG’s, as it yielded excellent NRMSE’s around 1.61%
for normal sounds and 5.19% for pathological
murmurs. less
In this paper, we address the Heart Sound signal
modeling problem. The approach taken is based on
sparse and redundant representations on an
overcomplete dictionary. We apply matching pursuit
(MP) and orthogonal matching pursuit ... more |
خرید مقاله
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