Results 221 to 230 of about 2,425,653 (248)
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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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Causal Segment Regression with Multiple Thresholds
Statistics and ComputingzbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Realistic Predictors for Regression and Semantic Segmentation
2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA), 2023Krishna Chaitanya Gadepally +3 more
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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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A Regression Model for Market Segmentation Studies
Journal of Marketing Research, 1980A model is developed for incorporating the long-standing marketing research effort of explaining variation in observed consumption behavior into the more recent notion that such behavior has an inherent component of randomness. The model recognizes that consumption behavior on any given occasion will fluctuate around some mean consumption level and ...
Albert R. Wildt, John M. Mccann
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Boundary Regression for Human Vertebrae Segmentation
2019 9th International Conference on Advances in Computing and Communication (ICACC), 2019The diagnosis and treatment of pathologies like Low back pain, Osteoporosis, Spondyflolisthesis etc. require detailed analysis of spinal images. Manual segmentation of vertebrae in spinal images is difficult. In this paper we discuss an automatic method for segmentation of vertebrae.
M.A Ancy Brigit +2 more
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Optimal segmentation of signals in a linear regression framework
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991The problem of estimating the time instants when the dynamical properties of a signal make abrupt changes is studied. This segmentation problem is usually considered as exponential in time. The author presents a specific but natural signal mode-called a changing regression model-and points out a method to compute an optimal estimate of the segmentation
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Sparse regressions for joint segmentation and linear prediction
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014Regularizing the least-squares criterion with the total number of coefficient changes, it is possible to estimate time-varying (TV) autoregressive (AR) models with piecewise-constant coefficients. Such models emerge in various applications including speech segmentation using linear predictors.
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Spontaneous Regression of Segmental Arterial Mediolysis
Journal of Vascular and Interventional Radiology, 2020Pupulim LF, Terraz S
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Segmented Cox Regression (60 Patients)
2012Cox regression assesses time to events, like death or cure, and the effects of predictors like comorbidity and frailty. If a predictor is not significant, then time-dependent Cox regression may be a relevant approach. It assesses whether the predictor interacts with time. Time dependent Cox has been explained in Chap. 56.
Ton J. Cleophas, Aeilko H. Zwinderman
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