Results 211 to 220 of about 331,169 (261)
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Analysis of the electroencephalogram of children by histogram method
Electroencephalography and Clinical Neurophysiology, 1958Abstract For the quantitative expression of slow activity of the EEG, the writers analysed the EEGs of 87 children by analyser and histogram methods and two of these EEGs were also analysed by the mathematical method. The histogram method was also applied to the study comparing EEGs of children having sign of some neuropsychiatric condition with ...
B, FUJIMORI +3 more
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Recursive region segmentation by analysis of histograms
ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005Recursive segmentation of an image into regions using histograms is one of the most widely used techniques for image segmentation. At CMU, several versions of a region segmentation program have been developed based on this technique (Ohlander, Price, Shafer and Kanade).
Steven A. Shafer, Takeo Kanade
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Histograms in symbolic data analysis
Annals of Operations Research, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Optimized convergence for multiple histogram analysis
Journal of Computational Physics, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tristan Bereau, Robert H. Swendsen
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Fuzzy histograms: A Statistical Analysis. [PDF]
, 2005 Fuzzy histograms are a fuzzy generalization of ordinary crisp histograms. In this paper, fuzzy histograms are analyzed statistically and are compared with other nonparametric density estimators. It turns out that fuzzy histograms can be used to combine a high level of statistical efficiency with a high level of computational efficiency.
Waltman, L.R. +2 more
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Convex Clustering Analysis for Histogram-Valued Data
Biometrics, 2018Abstract In recent years, there has been increased interest in symbolic data analysis, including for exploratory analysis, supervised and unsupervised learning, time series analysis, etc. Traditional statistical approaches that are designed to analyze single-valued data are not suitable because they cannot incorporate the additional ...
Cheolwoo Park +4 more
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A Bounding Histogram Approach for Network Performance Analysis
2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, 2013We analyze the performance of a network under general traffics derived from traces. We apply stochastic comparisons in order to derive bounding histograms with a reduced size and complexity. We prove some stochastic monotonicity properties for the network elements, in order to derive bounds on the performance measures such as delays and losses. We show
Ait Salaht, Farah +3 more
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Information granules in image histogram analysis
Computerized Medical Imaging and Graphics, 2018A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced.
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An Analysis of Histogram-Based Thresholding Algorithms
CVGIP: Graphical Models and Image Processing, 1993Abstract Eleven histogram-based global thresholding algorithms are presented in a common notational framework. Relationships among them are identified from 654 mixtures of two Gaussian distributions, plus effects of mixed pixels. The iterated version of Kittler and Illingworth′s minimum error algorithm ( Pattern Recognition , 19, 1986, 41-47) is ...
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Evaluating Retrieval Models through Histogram Analysis
Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015We present a novel approach for efficiently evaluating the performance of retrieval models and introduce two evaluation metrics: Distributional Overlap (DO), which compares the clustering of scores of relevant and non-relevant documents, and Histogram Slope Analysis (HSA), which examines the log of the empirical distributions of relevant and non ...
Kriste Krstovski +2 more
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