Results 251 to 260 of about 4,521,941 (297)
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Applied Optics, 1968
Very large bandwidths are required for the transmission of holographic data for systems such as TV. This paper presents a technique in which the large bandwidths normally required are traded off for either increased noise or decreased resolution in the image.
K A, Haines, D B, Brumm
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Very large bandwidths are required for the transmission of holographic data for systems such as TV. This paper presents a technique in which the large bandwidths normally required are traded off for either increased noise or decreased resolution in the image.
K A, Haines, D B, Brumm
openaire +2 more sources
Efficient data reduction in multimedia data
Applied Intelligence, 2006As the amount of multimedia data is increasing day-by-day thanks to cheaper storage devices and increasing number of information sources, the machine learning algorithms are faced with large-sized datasets. When original data is huge in size small sample sizes are preferred for various applications.
Surong Wang +3 more
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Computer Graphics and Image Processing, 1982
Abstract The problem of data reduction (sifting) of planar point series is approached from an information theoretical angle. It is concluded that effective data reduction can be achieved only when there exists a complementary relationship between the data reduction algorithm and the subsequent interpolation algorithm.
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Abstract The problem of data reduction (sifting) of planar point series is approached from an information theoretical angle. It is concluded that effective data reduction can be achieved only when there exists a complementary relationship between the data reduction algorithm and the subsequent interpolation algorithm.
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2011
This chapter discusses several data reduction techniques that are important in intrusion detection and prevention. Network traffic data includes rich information about system and user behavior, but the raw data itself can be difficult to analyze due to its large size.
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This chapter discusses several data reduction techniques that are important in intrusion detection and prevention. Network traffic data includes rich information about system and user behavior, but the raw data itself can be difficult to analyze due to its large size.
+4 more sources
2020
Before data analysis can commence, the raw experimental data collected in each individual neutron detector needs to be ‘reduced’; a process that involves applying a standard set of mathematical procedures to correct for, or remove, unwanted instrument, scattering and/or source contributions.
Nandita Sengupta, Jaya Sil
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Before data analysis can commence, the raw experimental data collected in each individual neutron detector needs to be ‘reduced’; a process that involves applying a standard set of mathematical procedures to correct for, or remove, unwanted instrument, scattering and/or source contributions.
Nandita Sengupta, Jaya Sil
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2007
This chapter contains an account of the processes applied to the raw scans, after the observations were completed, to transform them into a set of corrected spectra, suitable for the extraction of parameters to compare with theory, together with some preliminary observations on the data.
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This chapter contains an account of the processes applied to the raw scans, after the observations were completed, to transform them into a set of corrected spectra, suitable for the extraction of parameters to compare with theory, together with some preliminary observations on the data.
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Proceedings of the Python in Science Conference, 2023
Haoyin Xu, Haw-minn Lu, José Unpingco
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Haoyin Xu, Haw-minn Lu, José Unpingco
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2020
Data reduction in data mining selects/generates the most representative instances in the input data in order to reduce the original complex instance space and better define the decision boundaries between classes. Theoretically, reduction techniques should enable the application of learning algorithms on large-scale problems.
Julián Luengo +4 more
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Data reduction in data mining selects/generates the most representative instances in the input data in order to reduce the original complex instance space and better define the decision boundaries between classes. Theoretically, reduction techniques should enable the application of learning algorithms on large-scale problems.
Julián Luengo +4 more
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2012
Abstract Lateral variations in the density of rocks cause variations in the gravity field measured at the surface, and our central problem in gravity exploration is to discover the nature of subsurface rocks, their constituents, their structure, and their distribution.
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Abstract Lateral variations in the density of rocks cause variations in the gravity field measured at the surface, and our central problem in gravity exploration is to discover the nature of subsurface rocks, their constituents, their structure, and their distribution.
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