Results 221 to 230 of about 85,833 (253)
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Burr regression and portfolio segmentation
Insurance: Mathematics and Economics, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Beirlant, Jan +3 more
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Segmented Linear Regression Trees
Acta Mathematica Sinica, English SerieszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zheng, Xiangyu, Chen, Songxi
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A fuzzy clusterwise regression approach to benefit segmentation
International Journal of Research in Marketing, 1989Abstract An algorithm for fuzzy clusterwise regression (FCR) is proposed which can be used for benefit segmentation within the framework of preference analysis. The method simultaneously estimates the models relating preference to product dimensions within each cluster, as well as the parameters indicating the degree of membership of subjects in ...
Wedel, M., Steenkamp, J.E.B.M.
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Image segmentation by correlation adaptive weighted regression
Neurocomputing, 2017Abstract Image segmentation aims to partition an image into several disjoint regions with each region corresponding to a visual meaningful object. It is a fundamental problem in image processing and computer vision. Recently, subspace clustering methods shows great potential in image segmentation.
Weiwei Wang 0005, Cui-Ling Wu
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Multiple regression estimation for motion analysis and segmentation
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541), 2005This paper describes multiple model estimation for motion analysis and segmentation (aka spatial partitioning), from point correspondences in two successive images. In motion analysis applications, available (training) data is generated by several unknown models (motions).
Vladimir Cherkassky +2 more
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DBRS2: dense boundary regression for semantic segmentation
Journal of Electronic Imaging, 2018Most of the current semantic segmentation approaches have achieved state-of-the-art performance relying on fully convolutional networks. However, the consecutive operations such as pooling or convolution striding lead to spatially disjointed object boundaries.
Jinfu Yang +3 more
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Segmented regression for spatio-spectral background estimation
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017We formulate hyperspectral target detection in terms of a local context by modeling the relationship of individual pixels with the annuli of pixels that surround them. A prediction of the center pixel in terms of the annulus pixels provides an estimate of the target-free pixel value, and this estimate can be used as a baseline against which a ...
James Theiler, Amanda Ziemann
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Applications of segmented regression models for biomedical studies
American Journal of Physiology-Endocrinology and Metabolism, 1996In many biological models, a relationship between variables may be modeled as a linear or polynomial function that changes abruptly when an independent variable obtains a threshold level. Usually, the transition point is unknown, and a major objective of the analysis is its estimation. This type of model is known as a segmented regression model.
N G, Berman +3 more
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Causal Segment Regression with Multiple Thresholds
Statistics and ComputingzbMATH Open Web Interface contents unavailable due to conflicting licenses.
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CT Prostate Deformable Segmentation by Boundary Regression
2014Automatic and accurate prostate segmentation from CT images is challenging due to low image contrast, uncertain organ motion, and variable organ appearance in different patient images. To deal with these challenges, we propose a new prostate boundary detection method with a boundary regression strategy for prostate deformable segmentation.
Yeqin Shao +3 more
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