نتایج جستجو برای: kde method
تعداد نتایج: 1630870 فیلتر نتایج به سال:
This paper presents an evolutionary wrapper method for feature selection that uses a non-parametric density estimation method and a Bayesian Classifier. Non-parametric methods are a good alternative for scarce and sparse data, as in Bioinformatics problems, since they do not make any assumptions about its structure and all the information come from data itself. Results show that local modeling ...
An uncertain (scalar, vector, tensor) field is usually perceived as a discrete random field with a priori unknown probability distributions. To compute derived probabilities, e.g. for the occurrence of certain features, an appropriate probabilistic model has to be selected. The majority of previous approaches in uncertainty visualization were restricted to Gaussian fields. In this paper we exte...
Accurately estimating home range and understanding movement behavior can provide important information on ecological processes. Advances in data collection and analysis have improved our ability to estimate home range and movement parameters, both of which have the potential to impact species conservation. Fitting continuous-time movement model to data and incorporating the autocorrelated kerne...
Wound closure with cultured skin substitutes results in epithelium that is consistently hypopigmented. Hypothetically, addition of human melanocytes to cultured skin grafts may result in normal pigmentation of healed skin. Skin substitutes were composed of human epidermal keratinocytes and melanocytes, dermal fibroblasts, and collagen-glycosaminoglycan substrates, and were incubated for 12 d in...
This paper considers the problem the improvement and application of the KDE Mean Shift tracking algorithm and data analysis in a migration study of MTLn3 cells. The aim is to convert cell migration videos into numeric description of changes in cell behavior. The choice of KDE Mean Shift Tracking is based on its robust and prominent performance in time-lapse studies compared to other algorithms....
This paper proposes a Bayesian RC-frame finite element model updating (FEMU) and damage state estimation approach using the nonlinear acceleration time history based on nested sampling. Numerical (FEM) parameters are selected through sampling, their probability density is estimated history. In first step, we estimate error standard deviation select FEM that required to be updated by FEMU. secon...
Title of dissertation: KEY-FRAME APPEARANCE ANALYSIS FOR VIDEO SURVEILLANCE Kyongil Yoon, Doctor of Philosophy, 2005 Dissertation directed by: Professor Larry Davis Department of Computer Science Tracking moving objects is a commonly used approach for understanding surveillance video. However, by focusing on only a few key-frames, it is possible to effectively perform tasks such as image segmen...
MATSim (Multi-Agent Transport Simulation Toolkit) is an open source large-scale agent-based transportation planning project applied to various areas like road transport, public freight regional evacuation, etc. BEAM (Behavior, Energy, Autonomy, and Mobility) framework extends enable powerful scalable analysis of urban systems. The agents from the simulation exhibit ‘mode choice’ behavior based ...
Biomedical signal monitoring and recording are an integral part of medical diagnosis treatment control mechanisms. For this, enhanced signals with appropriate peak preservation required. The OWA (OrderedWeighted Aggregation) Filter used in this paper helps non-linear filtering peaks for accurate diagnosis. Weights important aspect the filter, Gaussian method KDE (Kernel Density Estimation) func...
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