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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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