When using granular computing for problem solving, one can focus on a specific level of understanding without looking at unwanted details of subsequent (more precise) levels. We present a granular computing framework ...
详细信息
When using granular computing for problem solving, one can focus on a specific level of understanding without looking at unwanted details of subsequent (more precise) levels. We present a granular computing framework for growing hierarchical self-organizing maps. this approach is ideal since the maps are arranged in a hierarchical manner and each is a complete abstraction of a pattern within data. the framework allows us to precisely define the connections between map levels. Formulating a neuron as a granule, the actions of granule construction and decomposition correspond to the growth and absorption of neurons in the previous model. In addition, we investigate the effects of updating granules with new information on both coarser and finer granules that have a derived relationship. Called bidirectional update propagation, the method ensures pattern consistency among data abstractions. An algorithm for the construction, decomposition, and updating of the granule-based self-organizing map is introduced. With examples, we demonstrate the effectiveness of this framework for abstracting patterns on many levels. (C) 2009 Elsevier B.V. All rights reserved.
Clustering is a, widely used unsupervised data analysis technique in machinelearning. However, a common requirement amongst many existing clustering methods is that all pairwise distances between patterns must be com...
详细信息
ISBN:
(纸本)9783642040306
Clustering is a, widely used unsupervised data analysis technique in machinelearning. However, a common requirement amongst many existing clustering methods is that all pairwise distances between patterns must be computed in advance. this makes it computationallly expensive and difficult to cope with large scale data used in several applications, such as in bioinformatics. In this paper we propose a novel sequential hierarchical clustering technique that initially builds a hierarchical tree from a small fraction of the entire data, while the remaining data is processed sequentially and the tree adapted constructively. Preliminary results using this approach show that the quality of the clusters obtained does not degrade while reducing the computational needs.
there exist several music composition systems that generate blues chord progressions, jazz improvisation, or classical pieces. Such systems often work by applying a set of rules explicitly provided to the system to de...
详细信息
this work presents an image analysis framework driven by emerging evidence and constrained by the semantics expressed in an ontology. Human perception, apart from visual stimulus and patternrecognition, relies also o...
详细信息
ISBN:
(纸本)9783642030697
this work presents an image analysis framework driven by emerging evidence and constrained by the semantics expressed in an ontology. Human perception, apart from visual stimulus and patternrecognition, relies also on general knowledge and application context for understanding visual content in conceptual terms. Our work is an attempt to imitate this behavior by devising an evidence driven probabilistic, inference framework using ontologies and bayesian networks. Experiments conducted for two different image analysis, tasks showed improvement performance, compared to the case where computer vision techniques act isolated from any type of knowledge or context.
With widespread use of microarray technology as a potential diagnostics tool, the comparison of results obtained from the use of different platforms is of interest. When inference methods are designed using data colle...
详细信息
ISBN:
(纸本)9783642040306
With widespread use of microarray technology as a potential diagnostics tool, the comparison of results obtained from the use of different platforms is of interest. When inference methods are designed using data collected using a particular platform, they are unlikely to work directly on measurements taken from a different type of array. We report on this cross-platform transfer problem, and show that, working with transcriptome representations at binary numerical precision, similar to the gene expression bar code method, helps circumvent the variability across platforms in several cancer classification tasks. We compare our approach with a recent machinelearning method specifically designed for shifting distributions, i.e., problems in which the training and testing data are not, drawn from identical probability distributions, and show superior performance in three of the four problems in which we could directly compare.
Compounds in drug screening-libraries should resemble pharmaceuticals. To operationally test this, we analysed the compounds in terms of known drug-like filters and developed a novel machinelearning method to discrim...
详细信息
ISBN:
(纸本)9783642040306
Compounds in drug screening-libraries should resemble pharmaceuticals. To operationally test this, we analysed the compounds in terms of known drug-like filters and developed a novel machinelearning method to discriminate approved pharmaceuticals from "drug-like" compounds. this method uses both structural features and molecular properties for discrimination. the method has an estimated accuracy of 91% in discriminating between the Maybridge Hit-Finder library and approved pharmaceuticals, and 99% between the NATDiverse collection (from Analyticon Discovery) and approved pharmaceuticals. these results show that Lipinski's Rule of 5 for oral absorption is not Sufficient to describe "drug-likeness" and be the main basis of screening-library design.
It is fundamental work to translate the historical characters called "kuzushi-ji" into the contemporary characters in Japanese historical studies. In this paper, we develop the japanese historical character ...
详细信息
the proceedings contain 65 papers. the topics discussed include: inference and learning for active sensing, experimental design and control;large scale online learning of image similarity through ranking;inpainting id...
详细信息
ISBN:
(纸本)3642021719
the proceedings contain 65 papers. the topics discussed include: inference and learning for active sensing, experimental design and control;large scale online learning of image similarity through ranking;inpainting ideas for image compression;smoothed disparity maps for continuous American sign language recognition;human action recognition using optical flow accumulated local histograms;trajectory modeling using mixtures of vector fields;high speed human detection using a multiresolution cascade of histograms of oriented gradients;face-to-face social activity detection using data collected with a wearable device;estimating vehicle velocity using Image profiles on rectified images;kernel based multi-object tracking using gabor functions embedded in a region covariance matrix;and autonomous configuration of parameters in robotic digital cameras.
Approach for multiple pattern extraction from obtained individual clusters is presented in this paper. pattern extraction supports the end users in understanding the cluster concept. pattern discovery approach uses re...
详细信息
Pervasive healthcare applications help to improve elderly and needy persons habitability by assisting them in living autonomously, and letting them participate in social communities and family life. these applications...
详细信息
ISBN:
(纸本)9788374934701
Pervasive healthcare applications help to improve elderly and needy persons habitability by assisting them in living autonomously, and letting them participate in social communities and family life. these applications are often highly complex. the data gained from many wireless sensors running on different sensor platforms is usually further processed and interpreted by machinelearning and patternrecognition components. the complexity of these systems stems from different types of environmental and vital parameters, different sampling rates, heterogeneous sensor platforms, unreliable network connections, as well as different programming languages that must be tailored to the use-case and the application environment. For further development decisions and to improve existing pervasive healthcare applications is the analysis and evaluation of known approaches a well known method. In this paper we present an evaluation framework for pervasive healthcare applications, which allows us to separate different approaches and discuss important aspects.
暂无评论