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An improved shots clustering key-frame extraction algorithm based on entropy is presented. Using the color information in the video frames, the algorithm looks every frame of a shot as a special sample and selects appropriate feature. And then through the improvement of the clustering analysis of video sequences to acquire the center value of various classes and the membership degree of every sample...
In this paper, we propose a novel model for unsupervised Chinese event extraction. We use a multi-information fusion technique to combine two kinds of information for knowledge representation of event instances: language features and structure information. Then, we perform our proposed XLS-means Clustering Algorithm to group the candidate event instances into a "natural" number of clusters,...
Abstract-Scientific and technical literature is a useful resource where people can extract interesting knowledge or patterns by text mining tools. Text mining technologies have been widely used to reveal topics and the structure of topics. In this paper, the selected articles in the form of textual data are represented by the network structure at first, and then text clustering algorithm is applied...
Texture segmentation by Pseudo Jacobi -Fourier moments is presented in this paper. Given a window size, moments for each pixel in the image are computed within small local windows, and then texture feature images be obtained by using a nonlinear transducer. Finally, each pixel in the image is classified by K-mean clustering algorithm.
This paper proposes a new method to cluster law texts based on referential relation of laws. We extract law entities (an entity represents a law) and their referential relation from law texts. Then SimRank algorithm is applied to calculate law entity's similarity through referential relation and law clustering is carried out based on the SimRank similarity. This is the first time to apply SimRank...
We propose an automatic moment-based image recognition technique in this paper. The problem to be solved consists of classifying the images from a set, using the content similarity. In the feature extraction stage, we compute a set of feature vectors using area moments. An automatic unsupervised feature vector classification approach is proposed next. It uses a hierarchical agglomerative clustering...
Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases. It is increasingly evident that an image retrieval system has to be domain specific. In this paper, we present an algorithm...
Artificial neural networks (ANN) and fuzzy systems are the widely preferred artificial intelligence techniques for biological computational applications. While ANN is less accurate than fuzzy logic systems, fuzzy theory needs expertise knowledge to guarantee high accuracy. Since both the methodologies possess certain advantages and disadvantages, it is primarily important to compare and contrast these...
This paper intends to propose a novel clustering method based on ant colony (AC) algorithm. A new approach called TT-transform based time frequency analysis is used in processing the non-stationary power signal disturbances. The time-time transform is the inverse Fourier transform of S-transform. The proposed model is demonstrated using feature vector from the domain of power signal analysis, yielding...
In this paper, we present an intelligent approach to analysing prostrate ultrasound images in order to diagnose prostate cancer. Algorithms based on fuzzy image processing are applied first to enhance the contrast of the original image, to extract the region of interest and to enhance the edges surrounding that region. Then, we extract features characterising the underlying texture of the regions...
Designing an OCR system for Indian languages in general is more complex than those of European languages due the linguistic complexity. Efforts are on the way for the development of efficient OCR systems for Indian languages, especially for Telugu, a popular South Indian language. In this paper, we proposed a method for reliable extraction of text line, word and character from document images of Telugu...
An improved clustering method used for cascaded intrusion detection is proposed in this paper. It can detect different kinds of intrusions by arranging the processing framework in a cascaded way, based on which we can abstract corresponding features to achieve clustering. Computer simulations based on the 1999 KDD CUP dataset show the effectiveness of the proposed approach in detecting various intrusions...
In this paper, it is described a new unsupervised approach based on wavelet packet transform for texture images segmentation. This transform is able to decompose an image not only from the low frequency parts, but also from the middle-high frequency parts, in which there is a certain amount of texture information. After the extraction of the features, a clustering is carried out, by using an immune-inspired...
Several general-purpose algorithms and techniques have been developed for image segmentation. Since there is no general solution to the image segmentation problem, these techniques often have to be combined with domain knowledge in order to effectively solve an image segmentation problem for a problem domain. This paper presents a comparative study of the basic image segmentation techniques i.e. edge-based,...
A novel approach for the extraction of rectangular boundaries from aerial image data is proposed and presented in this paper. In this approach, a centroid neural network (CNN) with a metric of line segments is also proposed for connecting low-level linear structures or grouping similar objects. Extracting rectangular boundaries for building rooftops from an edge image without height information of...
Clustering is used to find out the objects that resemble each other and compose different groups, cluster analysis is an important job in data mining. This article brings the rough set into fuzzy cluster, by using the methods of attributes contracted in the rough set theory to improve the FCM algorithm; the improved algorithm had been proved a high precise ratio.
Solving mathematical problems is both challenging and difficult for many students. This paper proposes a document retrieval approach to help solve mathematical problems. The proposed approach is based on Kohonenpsilas Self-Organizing Maps for data clustering of similar mathematical documents from a mathematical document database. Based on a user query problem, similar mathematical documents with their...
Text clustering is an important task of text mining. The purpose of text clustering is grouping similar text documents together efficiently to meet human interests in information searching and understanding. The procedure of clustering should involve a cognitive process of text understanding or comprehension.This paper introduces an innovative research effort, CogHTC, a hierarchical text clustering...
Based on a parametric planar rotation updated algorithm and the deflation technique, a blind signal extraction method is proposed in underdetermined mixtures. While extracting one, source signal from the mixtures and keeping size of the mixtures, a separated signal is concealed from the mixtures using the deflation technique. This procedure is repeated for the deflated mixtures until all source signals...
High-dimensional feature space affects the quality and efficiency of text categorization. This paper investigates an improved genetic algorithm that how to help select relevant features in text classification. We follow the so-called "region growing" method to initialize the population, and uses k-means algorithm to selection operation to control the scope of the search, ensure the validity...
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