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Paper Title |
Authors |
Conference |
Abstract |
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A New Evolutionary Algorithm for Structure Learning in Bayesian Networks |
A. R. Khanteymoori
M. B. Menhaj
M. M. Homayounpour
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
A new structure learning approach for Bayesian
networks (BNs) based on asexual reproduction
optimization (ARO) is proposed in this paper. ARO can
be essentially considered as an evolutionary based
algorithm that mathematically models the ... more
A new structure learning approach for Bayesian
networks (BNs) based on asexual reproduction
optimization (ARO) is proposed in this paper. ARO can
be essentially considered as an evolutionary based
algorithm that mathematically models the budding
mechanism of asexual reproduction. In ARO, a parent
produces a bud through a reproduction operator;
thereafter the parent and its bud compete to survive
according to a performance index obtained from the
underlying objective function of the optimization
problem; this leads to the fitter individual. The
proposed method is applied to real-world and
benchmark applications, while its effectiveness is
demonstrated through computer simulation. Results of
simulation show that ARO outperforms GA because
ARO results good structure in comparison with GA
and the speed of convergence in ARO is more than GA.
Finally, the ARO performance is statistically shown. less
A new structure learning approach for Bayesian
networks (BNs) based on asexual reproduction
optimization (ARO) is proposed in this paper. ARO can
be essentially considered as an evolutionary based
algorithm that mathematically models the ... more |
خرید مقاله
|
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A New Real-Time Target Tracking Algorithm in Image Sequences Based on Wavelet Transform |
A. Mehdi
R. R. Ggholam-ali
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
This paper estimates and segments the moving objects
based on center of mass model to decrease the search window
and to provide a new algorithm, which achieves an accurate
and rapid tracking.
Furthermore, a ... more
This paper estimates and segments the moving objects
based on center of mass model to decrease the search window
and to provide a new algorithm, which achieves an accurate
and rapid tracking.
Furthermore, a novel method is proposed to update the
template size adaptively by using estimation and segmentation
of moving objects. The estimated results of moving target is
transformed to wavelet domain and target tracking is
performed in that domain. To improve the algorithm center of
mass model is performed in wavelet domain. By using kalman
predictor and thresholding method, a new approach is
presented for object tracking failure and recovery. less
This paper estimates and segments the moving objects
based on center of mass model to decrease the search window
and to provide a new algorithm, which achieves an accurate
and rapid tracking.
Furthermore, a ... more |
خرید مقاله
|
|
Effective Tracking of the Players and Ball in Indoor Soccer Games in the Presence of Occlusion |
Soudeh Kasiri-Bidhendi
Reza Safabakhsh
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Object tracking is one of the major subjects in
machine vision and plays a main role in detection of
major events in indoor soccer matches. In this paper, a
novel approach for tracking ... more
Object tracking is one of the major subjects in
machine vision and plays a main role in detection of
major events in indoor soccer matches. In this paper, a
novel approach for tracking the ball and players is
proposed. In this method, the ground lines are
segmented and eliminated using a fast and effective
method. Then, the remaining non-field pixels are
considered and labeled as players and the ball. A fast
level set contour is used to track players and the ball.
The proposed method can track players and the ball in
presence of occlusion. Experiments show that the
proposed method is robust to occlusion and different
field colors. less
Object tracking is one of the major subjects in
machine vision and plays a main role in detection of
major events in indoor soccer matches. In this paper, a
novel approach for tracking ... more |
خرید مقاله
|
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Adaptive Target Tracking in Sensor Networks Using Reinforcement Learning |
Mohammad Rahimi
Reza Safabakhsh
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
This paper, proposes the use of a reinforcement
learning approach for a target tracking sensor network
application. Harsh and unpredictable situations of
sensor nodes in such an application requires a selftuning
mechanism for the ... more
This paper, proposes the use of a reinforcement
learning approach for a target tracking sensor network
application. Harsh and unpredictable situations of
sensor nodes in such an application requires a selftuning
mechanism for the nodes to adapt their
behavior over time. The method is examined under
high dynamic network conditions and compared with a
similar method called SORA over different
performance measures. The results show a significant
improvement over the compared method in the
environments with high level of dynamism. less
This paper, proposes the use of a reinforcement
learning approach for a target tracking sensor network
application. Harsh and unpredictable situations of
sensor nodes in such an application requires a selftuning
mechanism for the ... more |
خرید مقاله
|
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Support Vector Machines for Speaker Based Speech Indexing |
M. H. Moattar
M. M. Homayounpour
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
This paper proposes an integrated framework for
speaker indexing which includes both speaker
segmentation and speaker clustering. Speaker indexing
systems has wide domains of application with different
requirements which make a general speaker indexing
framework ... more
This paper proposes an integrated framework for
speaker indexing which includes both speaker
segmentation and speaker clustering. Speaker indexing
systems has wide domains of application with different
requirements which make a general speaker indexing
framework hard to accomplish. The main source of
performance degradation in speaker indexing is the
probable existence of short speech utterances which
makes the speaker turns hard to distinguish and also
exposes the segment modeling to data insufficiency.
This paper introduces a speaker indexing framework
with high average performance which uses Support
Vector Machines (SVM) as the core approach. The
main contribution of this framework is the SVM based
clustering approach which makes the indexing more
robust against the short speech segments. This
framework is evaluated on a domestic conversational
speech dataset and the results were satisfactory. less
This paper proposes an integrated framework for
speaker indexing which includes both speaker
segmentation and speaker clustering. Speaker indexing
systems has wide domains of application with different
requirements which make a general speaker indexing
framework ... more |
خرید مقاله
|
|
Speaker Clustering Performance Improvement using Eigen-Voice Speaker Adaptation |
M. H. Moattar
M. M. Homayounpour
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
One of the most important phases of speaker
indexing is speaker clustering which aims to find the
number of speakers in a speech document and merge
the speech segments corresponding to a single ... more
One of the most important phases of speaker
indexing is speaker clustering which aims to find the
number of speakers in a speech document and merge
the speech segments corresponding to a single speaker.
The most critical source of problem in speaker
clustering is the speech segments duration which may
be so short that proper segment modeling becomes
hard to achieve. An alternative suggestion in these
situations is to adapt global models with new data
instead of building the speaker models from the ground.
In this paper we investigate two adaptation techniques
in eigen-voice space for improving clustering
performance especially for shorter speech utterances.
These techniques were embedded in a clustering
framework and evaluated on a set of domestic
conversational speech. We have also compared the
proposed methods with some other known techniques.
The experiments show a considerable improvement in
speaker clustering performance. less
One of the most important phases of speaker
indexing is speaker clustering which aims to find the
number of speakers in a speech document and merge
the speech segments corresponding to a single ... more |
خرید مقاله
|
|
Face recognition using Local Multi Dimensional Statistics |
Roghayeh Alemy
Mohammad Ebrahim Shiri
Farzad Didehvar
Zaynab Hajimohammadi
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Though numerous approaches have been proposed
for face recognition. In this paper we propose a novel
face recognition approach based on adaptively
weighted patch Local Statistic in Multi dimensional
(LMDS) when only one exemplar ... more
Though numerous approaches have been proposed
for face recognition. In this paper we propose a novel
face recognition approach based on adaptively
weighted patch Local Statistic in Multi dimensional
(LMDS) when only one exemplar image per person is
available. In this approach, a face image is
decomposed into a set of equal-sized patches in a nonoverlapping
way. In order to obtain Local Multi
Dimensional Statistic Features in each patch, we
calculated mean and standard deviation of all pixels
along some directions. An adaptively weighting
scheme is used to assign proper weights to each
LMDS features to adjust the contribution of each
local area of a face in terms of the quantity of identity
information that a patch contains. An extensive
experimental investigation is conducted using AR face
databases covering face recognition under
controlled/ideal conditions and different facial
expressions. The system performance is compared
with the performance of four benchmark approaches.
The encouraging experimental results demonstrate
that our approach can be used for face recognition
and patch-based local statistic features provides a
novel way for face. less
Though numerous approaches have been proposed
for face recognition. In this paper we propose a novel
face recognition approach based on adaptively
weighted patch Local Statistic in Multi dimensional
(LMDS) when only one exemplar ... more |
خرید مقاله
|
|
English to Persian Machine Translation exploiting Semantic Word Sense Disambiguation |
Yasaman Motazedi
Mehnoush Shamsfard
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
PEnT1 is an automatic English to Persian text
translator. It translates simple English sentences into
Persian, exploiting a combination of rule based and
semantic approaches. It covers all the twelve tenses in
English in ... more
PEnT1 is an automatic English to Persian text
translator. It translates simple English sentences into
Persian, exploiting a combination of rule based and
semantic approaches. It covers all the twelve tenses in
English in both passive and active verbs for indicative,
negative, interrogative sentences. In this paper, introducing
PEnT1, we propose a new WSD method by presenting a
hybrid measure to score different senses of a word. We also
discuss prototyping some linguistic resources to test our
methods. less
PEnT1 is an automatic English to Persian text
translator. It translates simple English sentences into
Persian, exploiting a combination of rule based and
semantic approaches. It covers all the twelve tenses in
English in ... more |
خرید مقاله
|
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A Novel Vehicle Tracking Method with Occlusion Handling Using Longest Common Substring of Chain-Codes |
Elham Shabani Nia
Shohreh Kasaei
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Vehicle tracking is an essential requirement of any
vision based Intelligent Transportation System for
extracting different traffic parameters, efficiently.
Handling inter-object occlusion is the most
challenging part of tracking as a process of finding
and ... more
Vehicle tracking is an essential requirement of any
vision based Intelligent Transportation System for
extracting different traffic parameters, efficiently.
Handling inter-object occlusion is the most
challenging part of tracking as a process of finding
and following interested objects in a sequence of video
frames. In this paper we present a system, based on
code-book background model for motion segmentation
and Kalman filter for tracking with a new approach for
occlusion. This approach separates occluded vehicles
based on longest common substring of chain codes. We
use this tracking system to estimate some traffic
parameters. Experimental results show the efficiency
of the method less
Vehicle tracking is an essential requirement of any
vision based Intelligent Transportation System for
extracting different traffic parameters, efficiently.
Handling inter-object occlusion is the most
challenging part of tracking as a process of finding
and ... more |
خرید مقاله
|
|
High Maneuvering Target Tracking Using Fuzzy Fading Memory |
Mohamad Hasan Bahari
Asad Azemi
Naser Pariz
Said Khorashadi Zadeh
Seyed Mohsen Davarpanah
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, a new fuzzy fading memory (FFM) is
developed in order to aid a modified input estimation
(MIE) technique and enhance its performance in
tracking high maneuvering targets. The MIE has ... more
In this paper, a new fuzzy fading memory (FFM) is
developed in order to aid a modified input estimation
(MIE) technique and enhance its performance in
tracking high maneuvering targets. The MIE has been
introduced recently and performs well in tracking low
and medium maneuvering targets. However, due to
some modeling errors, the accuracy of this tracker may
be seriously degraded in presence of high maneuvers.
To cope with this difficulty, an intelligent approach
based on FFM is presented in this paper. Simulation
results prove the efficiency of the proposed method in
tracking high maneuvering targets. less
In this paper, a new fuzzy fading memory (FFM) is
developed in order to aid a modified input estimation
(MIE) technique and enhance its performance in
tracking high maneuvering targets. The MIE has ... more |
خرید مقاله
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