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Paper Title |
Authors |
Conference |
Abstract |
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A Multi-Role Cellular PSO for Dynamic Environments |
Ali B. Hashemi
M.R. Meybodi
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In real world, optimization problems are usually
dynamic in which local optima of the problem change.
Hence, in these optimization problems goal is not only
to find global optimum but also to track ... more
In real world, optimization problems are usually
dynamic in which local optima of the problem change.
Hence, in these optimization problems goal is not only
to find global optimum but also to track its changes. In
this paper, we propose a variant of cellular PSO, a
new hybrid model of particle swarm optimization and
cellular automata, which addresses dynamic
optimization. In the proposed model, population is
split among cells of cellular automata embedded in the
search space. Each cell of cellular automata can
contain a specified number of particles in order to
keep the diversity of swarm. Moreover, we utilize the
exploration capability of quantum particles in order to
find position of new local optima quickly. To do so,
after a change in environment is detected, some of the
particles in the cell change their role from standard
particles to quantum for few iterations. Experimental
results on moving peaks benchmark show that the
proposed algorithm outperforms mQSO, a well-known
multi swarm model for dynamic optimization, in many
environments. less
In real world, optimization problems are usually
dynamic in which local optima of the problem change.
Hence, in these optimization problems goal is not only
to find global optimum but also to track ... more |
خرید مقاله
|
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Particle Swarm Optimization with Voronoi Neighborhood |
Ehsan Safavieh
Amin Gheibi
Mohammadreza Abolghasemi
Ali Mohades
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Particle Swarm Optimization (PSO) is an
optimization method that is inspired by nature and is
used frequently nowadays. In this paper we proposed a
new dynamic geometric neighborhood based on
Voronoi diagram in PSO. ... more
Particle Swarm Optimization (PSO) is an
optimization method that is inspired by nature and is
used frequently nowadays. In this paper we proposed a
new dynamic geometric neighborhood based on
Voronoi diagram in PSO. Voronoi diagram is a
geometric naturalistic method to determine neighbors
in a set of particles. It seems that in realistic swarm,
particles take Voronoi neighbors into account.
Also a comparison is made between the
performance of some traditional methods for choosing
neighbors and new dynamic geometric methods like
Voronoi and dynamic Euclidean. In this comparison it
is found that PSO with geometric neighborhood can
achieve better accuracy overall especially when the
optimum value is out of the initial range. less
Particle Swarm Optimization (PSO) is an
optimization method that is inspired by nature and is
used frequently nowadays. In this paper we proposed a
new dynamic geometric neighborhood based on
Voronoi diagram in PSO. ... more |
خرید مقاله
|
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Real-Time Multiple Face Detection and Tracking |
Ahmad Ali Abin
Mehran Fotouhi
Shohreh Kasaei
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In recent years, processing the images that contain
human faces has been a growing research interest
because of establishment and development of
automatic methods especially in security applications,
compression, and perceptual user interface. In ... more
In recent years, processing the images that contain
human faces has been a growing research interest
because of establishment and development of
automatic methods especially in security applications,
compression, and perceptual user interface. In this
paper, a new method has been proposed for multiple
face detection and tracking in video frames. The
proposed method uses skin color, edge and shape
information, face detection, and dynamic movement
analysis of faces for more accurate real-time multiple
face detection and tracking purposes. One of the main
advantages of the proposed method is its robustness
against usual challenges in face tracking such as
scaling, rotation, scene changes, fast movements, and
partial occlusions. less
In recent years, processing the images that contain
human faces has been a growing research interest
because of establishment and development of
automatic methods especially in security applications,
compression, and perceptual user interface. In ... more |
خرید مقاله
|
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A New Similarity Difference Measure in Multi Agent Systems |
Monireh Abdoos
Nasser Mozayani
Ahmad Akbari
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, we present a new measure for
evaluating similarity changes in a multi agent system.
The similarity measure of the agents changes during
the learning process. The similarity differences are
because of ... more
In this paper, we present a new measure for
evaluating similarity changes in a multi agent system.
The similarity measure of the agents changes during
the learning process. The similarity differences are
because of any composition or decomposition of some
agent sets. The presented measure, defines the changes
of homogeneity of agents by composition and
decomposition. The utility of the metrics is
demonstrated in the experimental evaluation of multi
agent foraging. The results show that while the
similarity difference gets a positive value, the
performance grow rapidly. less
In this paper, we present a new measure for
evaluating similarity changes in a multi agent system.
The similarity measure of the agents changes during
the learning process. The similarity differences are
because of ... more |
خرید مقاله
|
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Various Strategies for Partitioning of Memeplexes in Shuffled Frog Leaping Algorithm |
A. Mashhadi Kashtiban
M. Alinia Ahandani
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper we propose several methods for
partitioning, the process of grouping members of
population to different memeplexes, in a shuffled frog
leaping algorithm. These proposed methods divide the
population in terms of ... more
In this paper we propose several methods for
partitioning, the process of grouping members of
population to different memeplexes, in a shuffled frog
leaping algorithm. These proposed methods divide the
population in terms of the value of cost function or the
geometric position of members or quite random
partitioning. The proposed methods are evaluated on
several low and high dimensional benchmark
functions. The obtained results on low dimensional
functions demonstrate that geometric partitioning
methods have the best success rate and the fastest
performance. Also on high dimensional functions,
however using of the geometric partitioning methods
for the partitioning stage of the SFL algorithm lead to
a better success rate but these methods are more time
consuming than other partitioning methods. less
In this paper we propose several methods for
partitioning, the process of grouping members of
population to different memeplexes, in a shuffled frog
leaping algorithm. These proposed methods divide the
population in terms of ... more |
خرید مقاله
|
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A New Distance Measure for Free Text Keystroke Authentication |
H. Davoudi
E. Kabir
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Keystroke dynamics-based authentication, KDA,
verifies users via their typing patterns. To authenticate
users based on their typing samples, it is required to
find out the resemblance of a typing sample and the
training samples ... more
Keystroke dynamics-based authentication, KDA,
verifies users via their typing patterns. To authenticate
users based on their typing samples, it is required to
find out the resemblance of a typing sample and the
training samples of a user regardless of the text typed.
In this paper, a measure is proposed to find the
distance between a typing sample and a set of samples
of a user. For each digraph, histogram-based density
estimation is used to find the pdf of its duration time.
This measure is combined with another measure which
is based on the two samples distances. Experimental
results show considerable decrease in FAR while FRR
remains constant. less
Keystroke dynamics-based authentication, KDA,
verifies users via their typing patterns. To authenticate
users based on their typing samples, it is required to
find out the resemblance of a typing sample and the
training samples ... more |
خرید مقاله
|
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Building Deep Dependency Structure from Partial Parses |
Heshaam Faili
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Increasing the domain of locality by using treeadjoining-
grammars (TAG) encourages some
researchers to use it as a modeling formalism in their
language application. But parsing with a rich
grammar like TAG faces two ... more
Increasing the domain of locality by using treeadjoining-
grammars (TAG) encourages some
researchers to use it as a modeling formalism in their
language application. But parsing with a rich
grammar like TAG faces two main obstacles: low
parsing speed and a lot of ambiguous syntactical
parses. We uses an idea of the shallow parsing based
on a statistical approach in TAG formalism, named
supertagging, which enhanced the standard POS tags
in order to employ the syntactical information about
the sentence. In this paper, an error-driven method in
order to approaching a full parse from the partial
parses based on TAG formalism is presented. These
partial parses are basically resulted from supertagger
which is followed by a simple heuristic based light
parser named light weight dependency analyzer
(LDA). Like other error driven methods, the process of
generation the deep parses can be divided into two
different phases: error detection and error correction,
which in each phase, different completion heuristics
applied on the partial parses. The experiments on Penn
Treebank show considerable improvements in the
parsing time and disambiguation process. less
Increasing the domain of locality by using treeadjoining-
grammars (TAG) encourages some
researchers to use it as a modeling formalism in their
language application. But parsing with a rich
grammar like TAG faces two ... more |
خرید مقاله
|
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A Watermarking Method Based on Optimizing SSIM Index by using PSO in DCT Domain |
Mohsen Rohani
Alireza Nasiri Avanaki
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
A watermarking method in DCT domain is
modified to achieve better imperceptibility. Particle
Swarm Optimization (PSO) is used to find the best
DCT coefficients for embedding the watermark
sequence and the Structural Similarity Index ... more
A watermarking method in DCT domain is
modified to achieve better imperceptibility. Particle
Swarm Optimization (PSO) is used to find the best
DCT coefficients for embedding the watermark
sequence and the Structural Similarity Index is used as
the fitness function in order to have a watermarked
image with the best possible quality. less
A watermarking method in DCT domain is
modified to achieve better imperceptibility. Particle
Swarm Optimization (PSO) is used to find the best
DCT coefficients for embedding the watermark
sequence and the Structural Similarity Index ... more |
خرید مقاله
|
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Hierarchical Bayesian Reservoir Memory |
Ali Nouri
Hooman Nikmehr
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In a quest for modeling human brain, we are going to introduce a brain model based on a general framework for brain called Memory-Prediction Framework. The model is a hierarchical ... more
In a quest for modeling human brain, we are going to introduce a brain model based on a general framework for brain called Memory-Prediction Framework. The model is a hierarchical Bayesian structure that uses Reservoir Computing methods as the state-of-the-art and the most biological plausible Temporal Sequence Processing method for online and unsupervised learning. So, the model is called Hierarchical Bayesian Reservoir Memory (HBRM). HBRM uses a simple stochastic gradient descent learning algorithm to learn and organize common multi-scale spatio-temporal patterns/features of the input signals in a hierarchical structure in an unsupervised manner to provide robust and real-time prediction of future inputs. We suggest HBRM as a real-time high-dimensional stream processing model for the basic brain computations. In this paper we will describe the model and assess its prediction accuracy in a simulated real-world environment. less
In a quest for modeling human brain, we are going to introduce a brain model based on a general framework for brain called Memory-Prediction Framework. The model is a hierarchical ... more |
خرید مقاله
|
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Speaker Identification in Noisy Environments Using Dynamic Bayesian Networks |
A. R. Khanteymoori
M. M. Homayounpour
M. B. Menhaj
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
This paper describes the theory and implementation
of dynamic Bayesian networks in the context of speaker
identification. Dynamic Bayesian networks provide a
succinct and expressive graphical language for
factoring joint probability distributions, and we ... more
This paper describes the theory and implementation
of dynamic Bayesian networks in the context of speaker
identification. Dynamic Bayesian networks provide a
succinct and expressive graphical language for
factoring joint probability distributions, and we begin
by presenting the structures that are appropriate for
doing speaker identification in clean and noisy
environments. This approach is notable because it
expresses an identification system using only the
concepts of random variables and conditional
probabilities. We present illustrative experiments in
both clean and noisy environments and our
experiments show that this new approach is very
promising in the field of speaker identification. less
This paper describes the theory and implementation
of dynamic Bayesian networks in the context of speaker
identification. Dynamic Bayesian networks provide a
succinct and expressive graphical language for
factoring joint probability distributions, and we ... more |
خرید مقاله
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