فا   |   En
Login
Paper Title Authors Conference Abstract
Bit-width Optimization of CS-ACELP Speech Coder by SIMULINK: Core Layer of the New G.729.1 Standard Zohre Sharifi Mehrjardi
Neda Kazemian Amiri
Sied Mehdi Fakhraie
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
In this work, we present SIMUIINK bit-true modeling of the conjugate structure-algebraic CELP (CS-ACELP) speech coder which has been chosen as the core layer of speech coder standard ITU-T G.729.1. The optimum bit numbers ... more
In this work, we present SIMUIINK bit-true modeling of the conjugate structure-algebraic CELP (CS-ACELP) speech coder which has been chosen as the core layer of speech coder standard ITU-T G.729.1. The optimum bit numbers of the computational blocks are defined as the minimum word-widths that maintain the quality of the output with minimum chip area and power. Such optimum bitwidth of the coefficients and the internal computations are extracted. As a result, a golden model of the codec which best suits as a reference for its hardware implementation is developed. The power and area improvements are estimated in two blocks of CSACELP speech coder. less
In this work, we present SIMUIINK bit-true modeling of the conjugate structure-algebraic CELP (CS-ACELP) speech coder which has been chosen as the core layer of speech coder standard ITU-T G.729.1. The optimum bit numbers ... more
خرید مقاله
Tensor-Based Face Representation and Recognition Using Multi-Linear Subspace Analysis Hadis Mohseni
Shohreh Kasaei
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
Discriminative subspace analysis is a popular approach for a variety of applications. There is a growing interest in subspace learning techniques for face recognition. Principal component analysis (PCA) and eigenfaces are two important subspace ... more
Discriminative subspace analysis is a popular approach for a variety of applications. There is a growing interest in subspace learning techniques for face recognition. Principal component analysis (PCA) and eigenfaces are two important subspace analysis methods have been widely applied in a variety of areas. However, the excessive dimension of data space often causes the curse of dimensionality dilemma, expensive computational cost, and sometimes the singularity problem. In this paper, a new supervised discriminative subspace analysis is presented by encoding face image as a high order general tensor. As face space can be considered as a nonlinear submanifold embedded in the tensor space, a decomposition method called Tucker tensor is used which can effectively decomposes this sparse space. The performance of the proposed method is compared with that of eigenface, Fisherface, tensor LPP, and ORO4×2 on ORL and Weizermann databases. Conducted experimental results show the superiority of the proposed method. less
Discriminative subspace analysis is a popular approach for a variety of applications. There is a growing interest in subspace learning techniques for face recognition. Principal component analysis (PCA) and eigenfaces are two important subspace ... more
خرید مقاله
Dynamic and memory efficient web page prediction model using LZ78 and LZW algorithms Alborz moghaddam
Ehsanollah kabir
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
Web access prediction has attracted significant attention in recent years. Web prefetching and some personalization systems use prediction algorithms. Most current applications that predict the next user web page have an offline component that ... more
Web access prediction has attracted significant attention in recent years. Web prefetching and some personalization systems use prediction algorithms. Most current applications that predict the next user web page have an offline component that does the data preparation task and an online section that provides personalized content to the users based on their current navigational activities. In this paper we present an online prediction model that does not have an offline component and fit in the memory with good prediction accuracy. Our algorithm is based on LZ78 and LZW algorithms that are adapted for modeling the user navigation in web. Our model decreases computational complexities which is a serious problem in developing online prediction systems. A performance evaluation is presented using real web logs. This evaluation shows that our model needs much less memory than PPM family of algorithms with good prediction accuracy. less
Web access prediction has attracted significant attention in recent years. Web prefetching and some personalization systems use prediction algorithms. Most current applications that predict the next user web page have an offline component that ... more
خرید مقاله
Facial Feature Detection and Extraction using Symmetry and Region-based Deformable Template Matching Hoda Bahonar
Nasrollah M. Charkari
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
In this paper, we propose a method for selecting the symmetry axis of eyes region from two or more candidates. We propose a region-based deformable template matching from two new defined operations: intensity-based 2-clustering ... more
In this paper, we propose a method for selecting the symmetry axis of eyes region from two or more candidates. We propose a region-based deformable template matching from two new defined operations: intensity-based 2-clustering and edge shadowing. The results display the effectiveness of our method for extraction of eye, eyebrow and nose templates. The parameters of these templates can be used as feature vectors in low bit rate transmission. Evaluation of the proposed method on an Iranian database shows the accuracy of 99% for feature region extraction and 86% in average for feature template extraction. less
In this paper, we propose a method for selecting the symmetry axis of eyes region from two or more candidates. We propose a region-based deformable template matching from two new defined operations: intensity-based 2-clustering ... more
خرید مقاله
A Contrast Independent Algorithm for Adaptive Binarization of Degraded Document Images M. valizadeh
M. komeili
N. armanfard
E. kabir
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
This paper presents an efficient algorithm for adaptive binarization of degraded document images. Document binarization algorithms suffer from poor and variable contrast in document images. We propose a contrast independent binarization algorithm that does not ... more
This paper presents an efficient algorithm for adaptive binarization of degraded document images. Document binarization algorithms suffer from poor and variable contrast in document images. We propose a contrast independent binarization algorithm that does not require any parameter setting by user. Therefore, it can handle various types of degraded document images. The proposed algorithm involves two consecutive stages. At the first stage, independent of contrast between foreground and background, some parts of each character are extracted and in the second stage, the gray level of foreground and background are locally estimated. For each pixel, the average of estimated foreground and background gray levels is defined as threshold. After extensive experiments, the proposed binarization algorithm demonstrate superior performance against four well-know binarization algorithms on a set of degraded document images captured with camera. less
This paper presents an efficient algorithm for adaptive binarization of degraded document images. Document binarization algorithms suffer from poor and variable contrast in document images. We propose a contrast independent binarization algorithm that does not ... more
خرید مقاله
Application of Neuro-Fuzzy models In Short Term Electricity Load Forecast A. R. Koushki
M. Nosrati Maralloo
C. Lucas
A. Kalhor
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
One of the important requirements for operational planning of electrical utilities is the prediction of hourly load up to several days, known as Short Term Load Forecasting (STLF). Considering the effect of its accuracy ... more
One of the important requirements for operational planning of electrical utilities is the prediction of hourly load up to several days, known as Short Term Load Forecasting (STLF). Considering the effect of its accuracy on system security and also economical aspects, there is an on-going attention toward putting new approaches to the task. Recently, Neuro Fuzzy modeling has played a successful role in various applications over nonlinear time series prediction. This paper presents a neuro-fuzzy model for the application of short-term load forecasting. This model is identified through Locally Liner Model Tree (LoLiMoT) learning algorithm. The model is compared to a multilayer perceptron and Kohonen Classification and Intervention Analysis. The models are trained and assessed on load data extracted from EUNITE network competition. less
One of the important requirements for operational planning of electrical utilities is the prediction of hourly load up to several days, known as Short Term Load Forecasting (STLF). Considering the effect of its accuracy ... more
خرید مقاله
Quantitative Similarity-based Evaluation of Text Retrieval Algorithms Parastoo Didari
Behrad Babai
Azadeh Shakery
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
Text retrieval engines, such as search engines, always return a list of documents in response to a given query. Existing evaluations of text retrieval algorithms mostly use Precision and Recall of the returned ... more
Text retrieval engines, such as search engines, always return a list of documents in response to a given query. Existing evaluations of text retrieval algorithms mostly use Precision and Recall of the returned list of documents as main quality measures of a search engine. In this paper, we propose a novel approach for comparing different algorithms adopted by different search engines and evaluate their performance. In our approach, the results of each algorithm is treated as an inter-related set of documents and the effectiveness of the algorithm is evaluated based on the degree of relation in the set of documents. After verifying the correctness of the evaluation measure by examining the results of the two retrieval algorithms, BM25 and pivoted normalization, and comparing these results with an ideal ranking, we compare the results of these algorithms and investigate the impact of certain major factors like stemming on the results of the suggested algorithm. The effectiveness of our proposed method is justified through obtained experimental results. less
Text retrieval engines, such as search engines, always return a list of documents in response to a given query. Existing evaluations of text retrieval algorithms mostly use Precision and Recall of the returned ... more
خرید مقاله
Polynomial Kernel Function and its Application in Locally Polynomial Neurofuzzy Models A. Shirvani
H. Chegini
S. Setayeshi
C. Lucas
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
Polynomials are one of the most powerful functions that have been used in many fields of mathematics such as curve fitting and regression. Low order polynomials are desired for their smoothness1, good local approximation ... more
Polynomials are one of the most powerful functions that have been used in many fields of mathematics such as curve fitting and regression. Low order polynomials are desired for their smoothness1, good local approximation and interpolation. Being smooth, they can be used to locally approximate almost any derivable function. This means that when linear functions fail in approximation (e.g. where the first order Taylor expansion equals zero) polynomial functions can be used in local approximation, such that one can achieve better estimations at extremums. In this paper, application of polynomial kernel functions in locally linear neurofuzzy models is shown. Using polynomial kernels in local models, better local approximations in prediction of chaotic time series such as Mackey-Glass is achieved, and the capability of the neurofuzzy network is enhanced. less
Polynomials are one of the most powerful functions that have been used in many fields of mathematics such as curve fitting and regression. Low order polynomials are desired for their smoothness1, good local approximation ... more
خرید مقاله
A New Classification Approach Based on Cooperative Game Atefeh Torkaman
Nasrollah Moghaddam Charkari
Mahnaz Aghaeipour
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
Classification is a well known task in data mining and machine learning that aims to predict the class of items as accurately as possible. A well planned data classification system makes essential data ... more
Classification is a well known task in data mining and machine learning that aims to predict the class of items as accurately as possible. A well planned data classification system makes essential data easy to find. An object is classified into one of the categories called classes according to the features that well separated the classes. Actually, classification maps an object to its classification label. Many researches used different learning algorithms to classify data; neural networks, decision trees, etc. In this paper, a new classification approach based on cooperative game is proposed. Cooperative game is a branch of game theory consists of a set of players and a characteristic function which specifies the value created by different subsets of the players in the game. In order to find classes in classification process, objects can be imagine as the players in a game and according to the values which obtained by these players, classes will be separated. This approach can be used to classify a population according to their contributions. In the other words, it applies equally to different types of data. Through out this paper, a special case in medical diagnosis was studied. 304 samples taken from human leukemia tissue consists of 17 attributes which determine different CD markers related to leukemia were analyzed. These samples collected from different types of leukemia at Iran Blood Transfusion Organization (IBTO). Obtained results demonstrate that cooperative game is very promising to use directly for classification. less
Classification is a well known task in data mining and machine learning that aims to predict the class of items as accurately as possible. A well planned data classification system makes essential data ... more
خرید مقاله
Feature integration for adaptive visual tracking in a particle filtering framework M. Komeili
N. Armanfard
M. Valizadeh
E. Kabir
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
In this paper we propose a new integration method for multi-feature object tracking in a particle filter framework. We divide particles into separate clusters. All particles within a cluster measure a specific feature. The ... more
In this paper we propose a new integration method for multi-feature object tracking in a particle filter framework. We divide particles into separate clusters. All particles within a cluster measure a specific feature. The number of particles within a cluster is in proportion to the reliability of associated feature. We do a compensation stage which neutralizes the effect of particles weights mean within a cluster. Compensation stage balances the concentration of particles around local maximal. So, particles are distributed more effectively in the scene. Proposed method provides both effective hypothesis generation and effective evaluation of hypothesis. Experimental results over a set of real-world sequences demonstrate better performance of our method compared to the common methods of feature integration. less
In this paper we propose a new integration method for multi-feature object tracking in a particle filter framework. We divide particles into separate clusters. All particles within a cluster measure a specific feature. The ... more
خرید مقاله
Conferences and Events





Registration in Computer Society of Iran
Search Papers