Results 41 to 50 of about 864,065 (266)
Unsupervised Image Segmentation Parameters Evaluation for Urban Land Use/Land Cover Applications
GeomaticsImage segmentation plays an important role in object-based classification. An optimal image segmentation should result in objects being internally homogeneous and, at the same time, distinct from one another.
Guy Blanchard Ikokou +1 more
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On Shrinkage Estimation for the Scale Parameter of Weibull Distribution
Data Science Journal, 2009 In the present article, some shrinkage testimators for the scale parameter of a two-parameter Weibull life testing model have been suggested under the LINEX loss function assuming the shape parameter is to be known.
Gyan Prakash, D C Singh, S K Sinha
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Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
Anomaly Detection Based on Markovian Geometric Diffusion
Machine Learning and Knowledge ExtractionAutomatic anomaly detection is vital in domains such as healthcare, finance, and cybersecurity, where subtle deviations may signal fraud, failures, or impending risks.
Erikson Carlos Ramos +2 more
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Uniqueness, scale, and resolution issues in groundwater model parameter identification
Water Science and Engineering, 2015 This paper first visits uniqueness, scale, and resolution issues in groundwater flow forward modeling problems. It then makes the point that non-unique solutions to groundwater flow inverse problems arise from a lack of information necessary to make the ...
Tian-chyi J. Yeh +6 more
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Unbiased Estimation of Location and Scale Parameters
The Annals of Mathematical Statistics, 1966 It is well-known that there is a close connection between linear functionals on an appropriate Banach space and unbiased estimators. In Section 2 we prove some results concerning unbiased estimation of location and scale parameters. As application of these results we consider the case of Cauchy density with unknown location [scale] but known scale ...
Ghosh, J. K., Singh, Rajinder
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Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Establishing a comprehensive apheresis medicine program in a resource‐constrained setting presents significant structural, financial, and logistical challenges. Despite the growing clinical importance of apheresis services globally, published experience from sub‐Saharan Africa remains sparse.
Folasade Adelekan‐Popoola +4 more
wiley +1 more source
Parameter‐adaptive nighttime image enhancement with multi‐scale decomposition
IET Computer Vision, 2016 As a challenging problem, image enhancement plays an important role in computer vision applications and has been widely studied. As one of the most difficult issues of image enhancement, outdoor nighttime image enhancement suffers from noise ...
Shuhang Wang, Jin Zheng, Bo Li
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One-Bit Quantization and Distributed Detection with an Unknown Scale Parameter
Algorithms, 2015 We examine a distributed detection problem in a wireless sensor network, where sensor nodes collaborate to detect a Gaussian signal with an unknown change of power, i.e., a scale parameter.
Fei Gao, Lili Guo, Hongbin Li, Jun Fang
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An empirical analysis of the shift and scale parameters in BatchNorm
Information Sciences, 2023 Batch Normalization (BatchNorm) is a technique that improves the training of deep neural networks, especially Convolutional Neural Networks (CNN). It has been empirically demonstrated that BatchNorm increases performance, stability, and accuracy, although the reasons for such improvements are unclear.
Peerthum, Yashna, Stamp, Mark
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