the proceedings contain 407 papers. the topics discussed include: block image retrieval based on a compressed linear Quadtree;a low complexity 2-power transform for video compression;a motion compensation method using...
ISBN:
(纸本)0780381858
the proceedings contain 407 papers. the topics discussed include: block image retrieval based on a compressed linear Quadtree;a low complexity 2-power transform for video compression;a motion compensation method using least squares motion estimation filter in wavelet domain;a histogram based adaptive vector filter for color image restoration;color appearance-based approach to robust tracking and recognition of multiple people;computational video editing model based on optimization with constraint-satisfaction;on the implementation of melody recognition on 8-bit and 16-bit microcontrollers;automatic localization and tracking of moving objects using adaptive snake algorithm;day markings detection in natural photo with morphological method;a user-attention based focus detection framework and its applications;video quality evaluation for wireless transmission with robust header compression;a novel low-complexity packetization method for fine-granularity scalable (FGS) video streaming;and cluster-dependent feature transformation with divergence-based out-of-handset rejection for robust speaker verification.
the proceedings contain 73 papers. the special focus in this conference is on Representation and Analysis. the topics include: Invariant recognition and processing of planar shapes;recent advances in structural patter...
ISBN:
(纸本)3540421203
the proceedings contain 73 papers. the special focus in this conference is on Representation and Analysis. the topics include: Invariant recognition and processing of planar shapes;recent advances in structural patternrecognition withapplications to visual form analysis;on learning the shape of complex actions;mereology of visual form;on matching algorithms for the recognition of objects in cluttered background;a fragment-based approach to object representation and classification;minimum-length polygons in approximation sausages;optimal local distances for distance transforms in 3D using an extended neighbourhood;independent modes of variation in point distribution models;qualitative estimation of depth in monocular vision;a new shape space for second order 3D-variations;spatial relations among pattern subsets as a guide for skeleton pruning;euclidean fitting revisited;on the representation of visual information;skeletons in the framework of graph pyramids;computational surface flattening;an adaptive image interpolation using the quadratic spline interpolator;the shock scaffold for representing 3D shape;curve skeletonization by junction detection in surface skeletons;representation of fuzzy shapes;skeleton-based shape models with pressure forces;a skeletal measure of 2D shape similarity;perception-based 2D shape modeling by curvature shaping and global topological properties of images derived from local curvature features.
thr main contribution of this paper is the development of polygon feature selection method for the classification of temporal data from two or more sources on the basis of quantifying structural changes with time. the...
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ISBN:
(纸本)0769507506;0769507514
thr main contribution of this paper is the development of polygon feature selection method for the classification of temporal data from two or more sources on the basis of quantifying structural changes with time. the study focuses on the analysis of EEG data. the paper shows results on the feature classification using a modified fuzzy nearest neighbour method. the transformed inputs are ideally suited for the effective classification of EEG data. the results show that the developed polygon feature selection method call be used robustly in signalapplications for source separation. recognition rates vary for each EEG channel data between 90-99% correct recognition. It is expected that several applications including time-series analysis, signalprocessing and speech recognition will benefit from the findings in this paper.
Artificial neural networks offer an alternative way to tackle complex and ill-defined problems. they can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are...
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Artificial neural networks offer an alternative way to tackle complex and ill-defined problems. they can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform predictions and generalisations at high speed. they have been used in diverse applications in control, robotics, patternrecognition, forecasting, medicine, power systems, manufacturing, optimisation, signalprocessing, and social/psychological sciences. they are particularly useful in system modelling, such as in implementing complex mapping and system identification. this paper presents various applications of neural networks in energy problems in a thematic rather than a chronological or any other way. Artificial neural networks have been used by the author in the field of solar energy;for modelling and design of a solar steam generating plant, for the estimation of a parabolic-trough collector's intercept factor and local concentration ratio and for the modelling and performance prediction of solar water-heating systems. they have also been used for the estimation of heating-loads of buildings, for the prediction of air flows in a naturally ventilated test room and for the prediction of the energy consumption of a passive solar building. In all such models, a multiple hidden-layer architecture has been used. Errors reported when using these models are well within acceptable limits, which clearly suggests that artificial neural-networks can be used for modelling in other fields of energy production and use. the work of other researchers in the field of energy is also reported. this includes the use of artificial neural-networks in heating, ventilating and air-conditioning systems, solar radiation, modelling and control of power-generation systems, load-forecasting and refrigeration. (C) 2000 Elsevier Science Ltd. All rights reserved.
Methods based on invariants can be used to recognize objects. In this paper, an invariant of points in stereo vision based on a reference point and two homographies is derived and compared withthe method recently pro...
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Methods based on invariants can be used to recognize objects. In this paper, an invariant of points in stereo vision based on a reference point and two homographies is derived and compared withthe method recently proposed by Shashua. the other invariant of lines in stereo vision based on one homography and one reference line is also derived. Although basically they still are cross ratios in projective geometry, they are very useful in vision applications.
In this paper, in the light of the criterion of minimum misclassified samples, a new kind of training algorithm for linear discriminant function is proposed based on the recognition results of all single features for ...
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In this paper, in the light of the criterion of minimum misclassified samples, a new kind of training algorithm for linear discriminant function is proposed based on the recognition results of all single features for training samples. there are two special construction algorithms, namely, the multidimensional direct method and the two-dimensional recursive method, designed for searching the optimal weight vector direction. In contrast to some traditional linear discriminant functions, the new training algorithm can be hardly influenced by the typicality and the quantity of training samples, in addition, it needs less amount of computation. the experimental results for patternrecognition of nuclear explosion show that the specific training algorithm is simple, practical and effective.
In recent years, cardiovascular pressure-volume relationship study is a very popular clinical and research topic for cardiologists. Although a lot of significant research results are published, many crucial problems r...
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In recent years, cardiovascular pressure-volume relationship study is a very popular clinical and research topic for cardiologists. Although a lot of significant research results are published, many crucial problems remain unsolved. the calculation and estimation of Equilibrium Volume (V0) of End-Diastolic iologists just cannot solve the EDPVR V0 problem properly. this study uses neural networks with different parameters to calculate V0's. the testing results demonstrate that the trained neural networks could process EDPVR's VCO data and produce V0 values accordingly. In many cases, neural networks generated better results than Simplex algorithm, and cardiologists confirmed the study positively. the proposed approach will find wide applications in cardiovascular research.
Development of human-machine dialog applications for messaging and information retrieval over the telephone pose stringent requirements on accuracy and speed of the automatic speech recognition (ASR) system. In this p...
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ISBN:
(纸本)0780335554
Development of human-machine dialog applications for messaging and information retrieval over the telephone pose stringent requirements on accuracy and speed of the automatic speech recognition (ASR) system. In this paper, we describe strategies for improved acoustic-phone modeling directed toward increasing recognition accuracy while maintaining the number of phone units low. Specifically, this paper considers: (1) the development of an improved set of head-tail context-dependent (CD) triphones. (2) A novel criterion for better selection of the number of states assigned to each phone unit based on the coefficient of variation measure of feature components in HMM-Gaussians. Performance of the models is evaluated using data that rep resent real telephony applications.
this paper reviews results from a number of field trials assessing speech recognition feasibility for telecommunications services. Several applications incorporating speech automation are explored: Directory Assistanc...
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ISBN:
(纸本)0780335554
this paper reviews results from a number of field trials assessing speech recognition feasibility for telecommunications services. Several applications incorporating speech automation are explored: Directory Assistance Call Completion (DACC), partial speech automation of Directory Assistance (OSF - Operator Store and Forward), banking over the telephone (Money Talks) and partial speech automation of a customer Calling center (PREVIU). the experimental results presented here were collected through Wizard-of-Oz experiments as feasibility precursors to speech recognition automation. Speech interfaces were clearly superior to Touch-Tone in one experiment (PREVIU), with caller participation increasing by 30%. In another experiment (Money Talks), speech recognition interfaces did not improve caller participation and, in fact, provided no advantages over Touch-Tone automation. A number of prompting strategies have been identified as advantageous in increasing caller participation and compliance in automated services. Ultimately, success with Speech automated services will rely on identifying the services most suitable for speech automation and then carefully crafting the user interface.
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