IEEE trans M 的文章，是关于体育视频的，它实现了，对精彩Shot的rank，很厉害啊
上传时间： 2014-01-02
上传用户：sxdtlqqjl
Part I provides a compact survey on classical stochastic geometry models. The basic models defined in this part will be used and extended throughout the whole monograph, and in particular to SINR based models. Note however that these classical stochastic models can be used in a variety of contexts which go far beyond the modeling of wireless networks. Chapter 1 reviews the definition and basic properties of Poisson point processes in Euclidean space. We review key operations on Poisson point processes (thinning, superposition, displacement) as well as key formulas like Campbell’s formula. Chapter 2 is focused on properties of the spatial Shot-noise process: its continuity properties, its Laplace transform, its moments etc. Both additive and max Shot-noise processes are studied. Chapter 3 bears on coverage processes, and in particular on the Boolean model. Its basic coverage characteristics are reviewed. We also give a brief account of its percolation properties. Chapter 4 studies random tessellations; the main focus is on Poisson–Voronoi tessellations and cells. We also discuss various random objects associated with bivariate point processes such as the set of points of the first point process that fall in a Voronoi cell w.r.t. the second point process.
标签： Stochastic Geometry Networks Wireless Volume and
上传时间： 2020-06-01
上传用户：shancjb
Much has been written concerning the manner in which healthcare is changing, with a particular emphasis on how very large quantities of data are now being routinely collected during the routine care of patients. The use of machine learning meth- ods to turn these ever-growing quantities of data into interventions that can improve patient outcomes seems as if it should be an obvious path to take. However, the field of machine learning in healthcare is still in its infancy. This book, kindly supported by the Institution of Engineering andTechnology, aims to provide a “snap- Shot” of the state of current research at the interface between machine learning and healthcare.
标签： Technologies Healthcare Learning Machine
上传时间： 2020-06-10
上传用户：shancjb
2.5 Neural Turing Machine - 2.1 Model - .DS_Store 10KB 2.4 RNN Sequence-to-Sequence Model - 2.8 One Shot Deep Learning - 2.7 Deep Transfer Learning Lifelong Learning especially for RL - 2.2 Optimization - 1.4 Speech Recognition Evolution - 1.2 Deep Belief Network(DBN)(Milestone of Deep Learning Eve) - 1.3 ImageNet Evolution（Deep Learning broke out from here） - 2.3 Unsupervised Learning Deep Generative Model - 2.6 Deep Reinforcement Learning
标签： MoldWizard 使用手册
上传时间： 2013-05-15
上传用户：eeworm
