993 resultados para Correlation (Statistics)
Resumo:
In the first part of this paper we show that a new technique exploiting 1D correlation of 2D or even 1D patches between successive frames may be sufficient to compute a satisfactory estimation of the optical flow field. The algorithm is well-suited to VLSI implementations. The sparse measurements provided by the technique can be used to compute qualitative properties of the flow for a number of different visual tsks. In particular, the second part of the paper shows how to combine our 1D correlation technique with a scheme for detecting expansion or rotation ([5]) in a simple algorithm which also suggests interesting biological implications. The algorithm provides a rough estimate of time-to-crash. It was tested on real image sequences. We show its performance and compare the results to previous approaches.
Resumo:
Humans recognize optical reflectance properties of surfaces such as metal, plastic, or paper from a single image without knowledge of illumination. We develop a machine vision system to perform similar recognition tasks automatically. Reflectance estimation under unknown, arbitrary illumination proves highly underconstrained due to the variety of potential illumination distributions and surface reflectance properties. We have found that the spatial structure of real-world illumination possesses some of the statistical regularities observed in the natural image statistics literature. A human or computer vision system may be able to exploit this prior information to determine the most likely surface reflectance given an observed image. We develop an algorithm for reflectance classification under unknown real-world illumination, which learns relationships between surface reflectance and certain features (statistics) computed from a single observed image. We also develop an automatic feature selection method.
Resumo:
In situ IR measurements for CO adsorption and preferential CO oxidation in H-2-rich gases over Ag/SiO2 catalysts are presented in this paper. CO adsorbed on the Ag/SiO2 pretreated with oxygen shows a band centered around 2169 cm(-1), which is assigned to CO linearly bonded to Ag+ sites. The amount of adsorbed CO on the silver particles ( manifested by an IR band at 2169 cm(-1)) depends strongly on the CO partial pressure and the temperature. The steady-state coverage on the Ag surface is shown to be significantly below saturation, and the oxidation of CO with surface oxygen species is probably via a non-competitive Langmuir Hinshelwood mechanism on the silver catalyst which occurs in the high-rate branch on a surface covered with CO below saturation. A low reactant concentration on the Ag surface indicates that the reaction order with respect to Pco is positive, and the selectivity towards CO2 decreases with the decrease of Pco. On the other hand, the decrease of the selectivity with the reaction temperature also reflects the higher apparent activation energy for H-2 oxidation than that for CO oxidation.
Resumo:
The silver catalyzed, selective catalytic reduction (SCR) of nitrogen oxides (NOx) by CH4, is shown to be a structure-sensitive reaction. Pretreatment has a great affect on the catalytic performances. Upon thermal treatment in inert gas stream, thermal induced changes in silver morphology lead to the formation of reduced silver species of clusters and particles. Catalysis over this catalyst indicates an initially higher activity but lower selectivity for the CH4-SCR of NOx Reaction induced restructuring of silver results in the formation of ill-defined silver oxides. This, in turn, impacts the adsorption properties and diffusivity of oxygen over silver catalyst, results in the decrease in activity but increase in selectivity of Ag-H-ZSM-5 catalyst for the CH4-SCR of NO.. (c) 2004 Elsevier B.V. All rights reserved.
Resumo:
This paper outlines a novel information sharing method using Binary Decision Diagrams (BBDs). It is inspired by the work of Al-Shaer and Hamed, who applied BDDs into the modelling of network firewalls. This is applied into an information sharing policy system which optimizes the search of redundancy, shadowing, generalisation and correlation within information sharing rules.
Resumo:
This paper defines a structured methodology which is based on the foundational work of Al-Shaer et al. in [1] and that of Hamed and Al-Shaer in [2]. It defines a methodology for the declaration of policy field elements, through to the syntax, ontology and functional verification stages. In their works of [1] and [2] the authors concentrated on developing formal definitions of possible anomalies between rules in a network firewall rule set. Their work is considered as the foundation for further works on anomaly detection, including those of Fitzgerald et al. [3], Chen et al. [4], Hu et al. [5], among others. This paper extends this work by applying the methods to information sharing policies, and outlines the evaluation related to these.
Resumo:
Janet Taylor, Ross D King, Thomas Altmann and Oliver Fiehn (2002). Application of metabolomics to plant genotype discrimination using statistics and machine learning. 1st European Conference on Computational Biology (ECCB). (published as a journal supplement in Bioinformatics 18: S241-S248).
Resumo:
Poolton, Nigel; Hamilton, B.; Evans, D.A., (2005) 'Synchrotron-laser pump-probe luminescence spectroscopy: Correlation of electronic defect states with x-ray absorption in wide-gap solids', Journal of Physics D: Applied Physics 38 pp.1478-1484 RAE2008