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Showing 1 to 7 of 7 for “"Marked point process"”.
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New marked point process models for microscopy images
… and biomedical engineering. As a result, image processing plays a critical role in this era of science and technology. In materials image analysis, image segmentation and feature detection are considered very important.</p> <p>The first part of this research aims to resolve the segmentation …
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COMBINING MARKOV RANDOM FIELD AND MARKED POINT PROCESS FOR MICROSCOPY IMAGE MODELING
In many microscopy image analysis applications, it is of critical importance to address
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Vacation queues with Markov schedules
… characterized by a queue length/server activity marked point process that is Markov renewal and a joint queue length/server activity process that is semi-regenerative. These processes allow characterization of both the transient and ergodic queueing behavior of vacation systems as seen …
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Spatial marked point processes: Models and inferences
<p>A spatial marked point process describes the locations of randomly distributed events in a region, with a mark attached to each observed point. Nowadays, the availability of spatiotemporal data is increasing and many spatiotemporal models are studied with applications in a wide range of …
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Clustering in Multidimensional Spaces with Applications to Statistics Analysis of Earthquake Clustering
… description following a model of Poisson marked point process in spatial and temporal dimensions is given. In this model, nearest-neighbor distance between earthquakes based on Baiesi and Paczuski's metric is found to follow Weibull distribution. Clustering is defined as deviation from …
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Error Resilient Video Coding Using Bitstream Syntax And Iterative Microscopy Image Segmentation
… bitstreams.</p> <p>A recent challenge in image processing is the analysis of biomedical images acquired using optical microscopy. Due to the size and complexity of the images, automated segmentation methods are required to obtain quantitative, objective and reproducible measurements of …
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Algorithms and inference for simultaneous-event multivariate point-process, with applications to neural data
The formulation of multivariate point-process (MPP) models based on the Jacod likelihood does not allow for simultaneous occurrence of events at an arbitrarily small time resolution. In this thesis, we introduce two versatile representations of a simultaneous event multivariate point-process …