Computer Assisted Visual Interactive recognition (CAVIAR) draws on sequential patternrecognition, image database, expert systems, pen computing, and digital camera technology. It is designed to recognize wild flowers...
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ISBN:
(纸本)076951695X
Computer Assisted Visual Interactive recognition (CAVIAR) draws on sequential patternrecognition, image database, expert systems, pen computing, and digital camera technology. It is designed to recognize wild flowers and other families of similar objects more accurately than machine vision and faster than most laypersons. the novelty of the approach is that human perceptual ability is exploited through interaction withthe image of the unknown object. the computer remembers the characteristics of all previously seen classes, suggests possible operator actions, and displays confidence scores based on already detected features. In one application, consisting of 80 test images of wild flowers, 10 laypersons averaged 80% recognition accuracy, at 12 seconds per flower.
Base IP mobility presents performance limitations when a mobile host increases its handoff rate between successive wireless points of attachment as a result of its mobility pattern. these limitations are augmented whe...
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Base IP mobility presents performance limitations when a mobile host increases its handoff rate between successive wireless points of attachment as a result of its mobility pattern. these limitations are augmented when latency externalities such as the round trip time between the mobile node and its peers, add to the total of latency and signalling overhead, impeding the performance of the mobility function. To alleviate that, IP mobility management has been extended by localised IP mobility management (LMM) functions focusing within the context of micromobility. this paper presents an investigation on performance issues for LMM. Based on generic principles derived from the effect of localising mobility control signalling, it explores the behaviour of the localisation effect of the mobility management entity.
the assumption that nonlinear rectifier loads contribute only to the steady state of a power system is commonly made in the design and analysis of power conditioners such as the shunt active filter. this tacitly assum...
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ISBN:
(纸本)0780376714
the assumption that nonlinear rectifier loads contribute only to the steady state of a power system is commonly made in the design and analysis of power conditioners such as the shunt active filter. this tacitly assumes that the nonlinear rectifier load is less sensitive than the AC system. this paper presents experimental measurements of the sensitivity of nonlinear rectifiers made by injecting a perturbing current into the point of coupling of the rectifier. the perturbing current is generated with a DSP controlled switching power converter typically used in shunt active filters. the DSP system also measures the change in the load current. Results are presented for both single-phase and three-phase rectifiers. these show that boththese rectifiers are sensitive to the perturbing current, that the response is measurable with relatively unsophisticated hardware and that the response has a well defined pattern in the frequencies that occur.
this Volume 1 of 3 of the conference proceedings contains 136 papers. Topics discussed include fuzzy filters for image processing, modeling with words, causality is undefinable toward a theory of hierarchical definabi...
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this Volume 1 of 3 of the conference proceedings contains 136 papers. Topics discussed include fuzzy filters for image processing, modeling with words, causality is undefinable toward a theory of hierarchical definability, patternrecognition and image processing, electronic and robotic systems, soft computing and hybrid systems, control systems and mathematics.
this Volume 2 of 3 of the conference proceedings contains 124 papers. Topics discussed include patternrecognition and image processing, electronic and robotic systems, soft computing and hybrid systems, control syste...
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this Volume 2 of 3 of the conference proceedings contains 124 papers. Topics discussed include patternrecognition and image processing, electronic and robotic systems, soft computing and hybrid systems, control systems, mathematics, uncertain rule based fuzzy logic systems for wireless communications, fuzzy controlled design, fuzzy optimization and decision making.
Classification of texture pattern is one of the most important problems in patternrecognition. In this paper, we present a classification method based on the Discrete Cosine Transform (DCT) coefficients of texture im...
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Classification of texture pattern is one of the most important problems in patternrecognition. In this paper, we present a classification method based on the Discrete Cosine Transform (DCT) coefficients of texture image. As the DCT works on gray level image, the color scheme of each image is transformed into gray levels. For classifying the images with DCT, we used two popular soft computing techniques namely neurocomputing and neuro-fuzzy computing. We used a feedforward neural network trained by backpropagation algorithm and an evolving fuzzy neural network to classify the textures. the soft computing models were trained using 80% of the texture data and remaining was used for testing and validation purposes. A performance comparison was made among the soft computing models for the texture classification problem. We also analyzed the effects of prolonged training of neural networks. It is observed that the proposed neuro-fuzzy model performed better than neural network.
the advances in Optical Character recognition (OCR) technology over the past decade have enabled the development of many automatic document-processing systems capable of 99% correct recognition on printed text. Howeve...
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Sequential pattern mining, which finds the set of frequent subsequences in sequence databases, is an important data-mining task and has broad applications. Usually, sequence patterns are associated with different circ...
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Sequential pattern mining, which finds the set of frequent subsequences in sequence databases, is an important data-mining task and has broad applications. Usually, sequence patterns are associated with different circumstances, and such circumstances form a multiple dimensional space. For example, customer purchase sequences are associated with region, time, customer group, and others. It is interesting and useful to mine sequential patterns associated with multi-dimensional information. In this paper, we propose the theme of multi-dimensional sequential pattern mining, which integrates the multidimensional analysis and sequential data mining. We also thoroughly explore efficient methods for multi-dimensional sequential pattern mining. We examine feasible combinations of efficient sequential pattern mining and multidimensional analysis methods, as well as develop uniform methods for high-performance mining. Extensive experiments show the advantages as well as limitations of these methods. Some recommendations on selecting proper method with respect to data set properties are drawn.
A call admission control mechanism is proposed to provide a consistent QoS guarantee for multimedia traffic on a mobile computing environment. An adaptive bandwidth reservation based on an MPP(mobility pattern profile...
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Proposes a fuzzy pattern verification system based on fuzzy if-then rules and fuzzy membership functions in fuzzy clustering. the proposed fuzzy system is applied to speaker verification and is compared with current p...
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Proposes a fuzzy pattern verification system based on fuzzy if-then rules and fuzzy membership functions in fuzzy clustering. the proposed fuzzy system is applied to speaker verification and is compared with current probabilistic verification systems. Experiments performed on the ANDOSL and YOHO speech corpora show better results for the proposed system.
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