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To obtain these features, an efficient implementation of finite impulse response (FIR) filter, with Variable Bandwidth and Fractional Delay, is proposed in this paper.
In order to obtain these features, attentions are not only focused on the method to combine signal sensing and power generating together, but also on the method to improve measurement accuracy.
Conventional lithography is not suited to obtain these features because of the resolution limits, so that previous alternative approaches have involved the use of electron beam lithography, focused ion beam lithography or scanning probe nanolithography.
In order to obtain these features, small particle size, narrow size distribution, uniform morphology, optimum crystallinity degree, high specific surface area, minimum defects, agglomeration, and homogeneous metal doping are required for the practical applications of CCTO powders.
To obtain these features each color channel of an image is subject to a parameter estimation of a GMRF.
In order to obtain these features, the first step was splitting the spectro-temporal FLIM data cube into different temporal FLIM cubes, one for each wavelength band.
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The process of obtaining these features from multispectral FLIM images is outlined in Fig. 3 and Fig. 4 respectively.
In order to obtain these 3D features, a new classifier associates an object class label to each moving region (e.g. person, vehicle), a parallelepiped model and visual reliability measures of its attributes.
The classification error obtained with these features was 50.1163%.
The second stage involves fusion of the matching scores obtained from these feature sets after applying the similarity measures as described in the previous section.
For this reason, the interpretability and generality of the QSAR/QSPR models obtained by these feature selection methods are drastically affected.
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