Multiple objects tracking and recognition technique with video image sequences incomplex traffic environment is one of the hot spots of intelligent traffic surveillance system inrecent years. It involves a wide range of technologies, including computer vision, imageprocessing and pattern recognition, artificial intelligence, communication etc. This papermainly focuses on multiple objects recognition, which is the important
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Multiple objects tracking and recognition technique with video image sequences incomplex traffic environment is one of the hot spots of intelligent traffic surveillance system inrecent years. It involves a wide range of technologies, including computer vision, imageprocessing and pattern recognition, artificial intelligence, communication etc. This papermainly focuses on multiple objects recognition, which is the important
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Since the face recognition had been proposed, it had always been paid somuch attention.From the cognitive perspective, the biomi metic patternrecognition method had overcome the samples partition problem that exited inthe traditional pattern recognition method. Though the study of a large numberof related literatures, we used the biomimetic pattern recognition theory,focusing on how to detect
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Pattern recognition is one of the most important areas of research and application on artificial intelligence. With the rapid development of artificial intelligence, pattern recognition accordingly has been widely used in many fields. However, owing to the traditional statistical pattern recognition regarding”optimal seperating”as its main principle, there exist many limitations. Hence, it is poor in
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With the advent of the Internet era, the amount of electronic data increases dramatically. Thus the problem on how to obtain, manage and make full use of the text data has become an urgent issue in information science. And Text classification(TC) is a very important research field of information technology, which categorize natural language texts
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As a popular existent image pattern, texture becomes important research problem of computer vision and image processing. People have proposed lots of feature extraction and classification algorithms and achieved great successful in the last few years, but there are also many algorithms based on tradition mode grader, so influence validity and velocity of classification algorithms
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Medical image segmentation is a hot issues and tough in the medical image processing and analysis field. Magnetic Resonance Imaging (MRI) is a medical imaging technique with noninvasive, high-resolution and clear anatomical structure. In the diagnosis of brain tissue, Magnetic Resonance Imaging has unique advantages, which has become a major clinical diagnostic technique. This paper
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Since the 9.11 incident, as people realize the importance of peace for the city-building, intelligent security monitoring technology has developed rapidly. In this thesis, as the current security monitoring through the use of video image analysis to achieve real-time monitoring and alarm exist deficiencies, so speech recognition technology is applied into intelligent security monitoring system
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Biometrics recognition technology has been in harmoney with our daily lives and play an increasingly important role with the development of one high degree of modern information society. One type of Biometrics recognition technology— iris recognition technology —with its own merits, for example, incomparable uniqueness, stability, reliability, security and so on decides its stature of
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In this paper, a method of feature extraction combines with LPCC and peak characteristics based on LPCC feature cxtraction. This feature extraction algorithm resolves the disadvantage of computational complexity of MFCC. According to this method build a speech recognition sample library. In the past, speech recognition methods are based on the traditional pattern recognition ones,
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