|
Paper Title |
Authors |
Conference |
Abstract |
|
|
A Learning Automata Based Artificial Immune System for Data Classification |
A. H. Momeni Azandaryani
M. R. Meybodi
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper we propose an artificial immune
system in which learning automata are used to
adaptively determine the values of its parameters.
Learning automata are used for altering the shape of
receptor portion ... more
In this paper we propose an artificial immune
system in which learning automata are used to
adaptively determine the values of its parameters.
Learning automata are used for altering the shape of
receptor portion of antibodies to better
complementarily match the confronted antigen. In
order to show the effectiveness of the proposed
artificial immune computer experiments have been
conducted. The result of experimentations confirms the
effectiveness of the proposed model. less
In this paper we propose an artificial immune
system in which learning automata are used to
adaptively determine the values of its parameters.
Learning automata are used for altering the shape of
receptor portion ... more |
خرید مقاله
|
|
Identification of Web Communities using Cellular Learning Automata |
S. Motiee
M. R. Meybodi
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
A collection of web pages which are
about a common topic and are created by
individuals or any kind of associations that have a
common interest on that specific topic is called a
web ... more
A collection of web pages which are
about a common topic and are created by
individuals or any kind of associations that have a
common interest on that specific topic is called a
web community. Since at present, the size of the
web is over 3 billion pages and it is still growing
very fast, identification of web communities has
become an increasingly hard task. In this paper, a
method based on asynchronous cellular learning
automata (ACLA) for identification of web
communities is proposed. In the proposed method
first an asynchronous cellular learning automaton
is used to determine the related pages and their
relevance degree (the relationship structure of web
pages). For determination of relationship structure
of web pages information about hyperlinks and the
users’ behaviour in visiting the web pages are
used. Then, an algorithm similar to the HITS
algorithm is applied on the obtained structure to
identify the web communities. One of the
advantages of the proposed method is that the web
community obtained using this method is not
dependent on a specific web graph structure. To
evaluate the proposed approach, it is implemented
and the results are compared with the results
obtained for two existing methods, HITS and a
complete bipartite graph based method.
Experimental results show the superiority of the
proposed method. less
A collection of web pages which are
about a common topic and are created by
individuals or any kind of associations that have a
common interest on that specific topic is called a
web ... more |
خرید مقاله
|
|
A Technique Based on Chaos for Brain Computer Interfacing |
A. Banitalebi
S. K. Setarehdan
G. A. Hossein-Zadeh
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
A user of Brain Computer Interface (BCI) system
must be able to control external computer devices with
brain activity. Although the proof-of-concept was
given decades ago, the reliable translation of user
intent into device ... more
A user of Brain Computer Interface (BCI) system
must be able to control external computer devices with
brain activity. Although the proof-of-concept was
given decades ago, the reliable translation of user
intent into device control commands is still a major
challenge. There are problems associated with
classification of different BCI tasks. In this paper we
propose the use of chaotic indices of the BCI. We use
largest Lyapunov exponent, mutual information,
correlation dimension and minimum embedding
dimension as the features for the classification of EEG
signals which have been released by BCI Competition
IV. A multi-layer Perceptron classifier and a KMSVM(
support vector machine classifier based on kmeans
clustering) is used for classification process,
which lead us to an accuracy of 95.5%, for
discrimination between two motor imagery tasks. less
A user of Brain Computer Interface (BCI) system
must be able to control external computer devices with
brain activity. Although the proof-of-concept was
given decades ago, the reliable translation of user
intent into device ... more |
خرید مقاله
|
|
Hybrid Feature and Decision Level Fusion of Face and Speech Information for Bimodal Emotion Recognition |
Muharram Mansoorizadeh
Nasrollah Moghaddam Charkari
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
A hybrid feature and decision level information fusion
architecture is proposed for human emotion recognition
from facial expression and speech prosody. An active buffer
stores the most recent information extracted from face and
speech. ... more
A hybrid feature and decision level information fusion
architecture is proposed for human emotion recognition
from facial expression and speech prosody. An active buffer
stores the most recent information extracted from face and
speech. This buffer allows fusion of asynchronous information
through keeping track of individual modality updates.
The contents of the buffer will be fused at feature level; if
their respective update times are close to each other. Based
on the classifiers’ reliability, a decision level fusion block
combines results of the unimodal speech and face based
systems and the feature level fusion based classifier. Experimental
results on a database of 12 people show that the
proposed fusion architecture performs better than unimodal
classification, pure feature level fusion and decision level
fusion. less
A hybrid feature and decision level information fusion
architecture is proposed for human emotion recognition
from facial expression and speech prosody. An active buffer
stores the most recent information extracted from face and
speech. ... more |
خرید مقاله
|
|
A New Wavelet Thresholding Method for Speech Enhancement Based on Symmetric Kullback-Leibler Divergence |
Shima Tabibian
Ahmad Akbari
Babak Nasersharif
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Performance of wavelet thresholding methods for
speech enhancement is dependent on estimating an
exact threshold value in the wavelet sub-bands. In this
paper, we propose a new method for more exact
estimating the threshold ... more
Performance of wavelet thresholding methods for
speech enhancement is dependent on estimating an
exact threshold value in the wavelet sub-bands. In this
paper, we propose a new method for more exact
estimating the threshold value. We proposed to
determine the threshold value based on the symmetric
Kullback-Leibler divergence between the probability
distributions of noisy speech and noise wavelet
coefficients. In the next step, we improved this value
using segmental SNR. We used some of TIMIT
utterances to assess the performance of the proposed
threshold. The algorithm is evaluated using the PESQ
score and the SNR improvement. In average, we obtain
2db SNR improvement and a PESQ score increase up
to 0.7 in comparison to the conventional wavelet
thresholding approaches. less
Performance of wavelet thresholding methods for
speech enhancement is dependent on estimating an
exact threshold value in the wavelet sub-bands. In this
paper, we propose a new method for more exact
estimating the threshold ... more |
خرید مقاله
|
|
Planning a Robust Path for Mobile Robots in Dynamic Environment |
Mahmood Naderan-Tahan
Mohammad Taghi Manzuri-Shalmani
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, we propose a new method for mobile
robot path planning in dynamic environment when the
trajectories of obstacles are unknown. Our algorithm
first utilizes a global approach called clearance based
probabilistic ... more
In this paper, we propose a new method for mobile
robot path planning in dynamic environment when the
trajectories of obstacles are unknown. Our algorithm
first utilizes a global approach called clearance based
probabilistic roadmap method to find a suitable path
and then locally apply evolutionary algorithm to keep
the structure of the path when obstacles collide with
the path. As a result, the path will act like an elastic
band. To reach real time applicability, a light fitness
function is proposed compare to other genetic
algorithms to reduce the computation time needed for
calculating and repairing path. Simulation results
show that our method not only can keep the original
structure of path, but also repair operation is done
quickly even in the scenes with many obstacles. less
In this paper, we propose a new method for mobile
robot path planning in dynamic environment when the
trajectories of obstacles are unknown. Our algorithm
first utilizes a global approach called clearance based
probabilistic ... more |
خرید مقاله
|
|
Skin Detection using Contourlet Texture Analysis |
Mehran Fotouhi
Mohammad H. Rohban
Shohreh Kasaei
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
A combined texture- and color-based skin detection
is proposed in this paper. Nonsubsampled contourlet
transform is used to represent texture of the whole
image. Local neighbor contourlet coefficients of a pixel
are used as ... more
A combined texture- and color-based skin detection
is proposed in this paper. Nonsubsampled contourlet
transform is used to represent texture of the whole
image. Local neighbor contourlet coefficients of a pixel
are used as feature vectors to classify each pixel.
Dimensionality reduction is addressed through
principal component analysis (PCA) to remedy the
curse of dimensionality in the training phase. Before
texture classification, the pixel is tested to determine
whether it is skin-colored. Therefore, the classifier is
learned to discriminate skin and non-skin texture for
skin colored regions. A multi-layer perceptron is then
trained using the feature vectors in the PCA reduced
space. The Markov property of images is addressed in
post-processing to join separate neighbor skin detected
regions. Comparison of the proposed method with
other state-of-the-art methods shows a lower false
positive rate with a little decrease in true positive rate. less
A combined texture- and color-based skin detection
is proposed in this paper. Nonsubsampled contourlet
transform is used to represent texture of the whole
image. Local neighbor contourlet coefficients of a pixel
are used as ... more |
خرید مقاله
|
|
Job-Shop Scheduling Using Hybrid Shuffled Frog Leaping |
M. Alinia Ahandani
N. Pourqorban Shirjoposht
R. Banimahd
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Job-shop scheduling problem is demonstrated as
one of the NP-complete problems. To solve this
problem, we propose two types of hybrid shuffled frog
leaping algorithm. Hybrid algorithms are generated by
combining the shuffled frog ... more
Job-shop scheduling problem is demonstrated as
one of the NP-complete problems. To solve this
problem, we propose two types of hybrid shuffled frog
leaping algorithm. Hybrid algorithms are generated by
combining the shuffled frog leaping and a local search
method. Also a new local search method by combining
two other simple local searches is proposed. The
obtained results demonstrate that our proposed hybrid
algorithms have a better performance than their nonhybrid
competitors. Also a comparison among
proposed hybrid shuffled frog leaping and hybrid
genetic algorithms demonstrate that the hybrid shuffled
frog leaping algorithms can be generated a better
schedule than their genetic algorithm competitors. A
caparison of the best obtained results with the results
reported in the considered literature shows that our
proposed algorithms have a comparable performance. less
Job-shop scheduling problem is demonstrated as
one of the NP-complete problems. To solve this
problem, we propose two types of hybrid shuffled frog
leaping algorithm. Hybrid algorithms are generated by
combining the shuffled frog ... more |
خرید مقاله
|
|
Robust Pupil Boundary Detection by Optimized Color Mapping for Iris Recognition |
Rasoul Kheirolahy
Hossein Ebrahimnezhad
MohammadHossein Sedaaghi
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Accurate pupil segmentation is the first and most
important step for an iris recognition system. Current
methods are based on fitting a model such as circle or
ellipse to find and detect pupil, ... more
Accurate pupil segmentation is the first and most
important step for an iris recognition system. Current
methods are based on fitting a model such as circle or
ellipse to find and detect pupil, while these methods
don’t have sufficient accuracy and are sensitive to the
specular spot reflection. In this paper, we utilize an
optimized color mapping to increase the accuracy of
pupil segmentation, regardless of pupil model and its
shape (circular or elliptic), while removing the effects
of specular spot reflection. The optimum color
mapping can be established by an iterative
minimization algorithm similar to Levenberg-
Marquardt (LM) method. By applying this method, a
new image is provided with a clear pupil region that
can be easily segmented. Also a robust preprocessing
step is presented in this paper that sharpens and clears
pupil region. We obtain 98% accuracy in pupil
boundary detection by applying this method on
UBIRIS dataset. Also, the proposed method works well
on any model of eye image even where the eye is not
perpendicular to the camera. less
Accurate pupil segmentation is the first and most
important step for an iris recognition system. Current
methods are based on fitting a model such as circle or
ellipse to find and detect pupil, ... more |
خرید مقاله
|
|
Deconvolution of Non-Minimum Phase FIR Systems Using Adaptive Filtering |
M. Lankarany
M.H. Savoji
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
We address, in this paper, the problem of estimating
the input sequence of a known, non-minimum phase,
FIR system, when a large number of its roots are
located near or on the unit ... more
We address, in this paper, the problem of estimating
the input sequence of a known, non-minimum phase,
FIR system, when a large number of its roots are
located near or on the unit circle. This issue cannot be
solved by conventional methods known to date.
Recently, algorithms based on spectral factorization
are considered as possible solutions of inversing nonminimum
phase systems but, these techniques cannot
prohibit the instability of the systems whose roots are
located on the unit circle. We propose an alternative
method based on adaptive filtering resulted from a new
point of view of the deconvolution problem that avoids
inversing the system. The LMS adaptive filter is used to
meet our objective while faster implementation than
optimization-based techniques, be it gradient based or
genetic, is achieved. Moreover, the technique is
validated by experimental results, in simulated cases,
which are mainly focused on large sequence of signals
in noisy conditions. less
We address, in this paper, the problem of estimating
the input sequence of a known, non-minimum phase,
FIR system, when a large number of its roots are
located near or on the unit ... more |
خرید مقاله
|
.gif){kind=icon}
