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Table 2 Feature sets defined for 3-D fluorescence microscope images.

in Journal of Biomedical Optics 9(5), 893–912 (September/October 2004) From quantitative microscopy to automated image understanding
by Kai Huang, Robert F. Murphy
"... In PAGE 5: ... While 2-D edge features can be extended to 3-D directly, for computa- tional convenience, two new features were designed from 2-D edges found in each 2-D slice of a 3-D image.5 Table2 shows all current 3-D features. Haralick texture features.... ..."

Table 1. Notation for EM for mixture of dynamic textures

in
by unknown authors
"... In PAGE 3: ...epends on hidden variables (i.e. there is missing data). For the dynamic texture mixture, the observed information is a set of video sequences {yi}, and the missing data consists of 1) the assignments of sequences to mixture components (the assignment of sequence yi to the jth mixture component is encoded by the state of the indicator variable z(j) i ), and 2) the hidden state sequence x(j) i for yi under component j (see Table1 for notation). The EM solution is found using an iterative procedure that alternates between estimating the missing information with the current parameters, and com- puting new parameters given the estimate of the missing in- formation.... ..."

Table 1 Lumen Ratings of Selected Fluorescent Lamps

in Full-Spectrum Polarized Lighting: An Option for Light Therapy Boxes
by Daniel Karpen Harbor, Daniel Karpen P. E
"... In PAGE 4: ...Page 9 Table1 below shows the scotopic and the photopic lumen ratings for a number of light sources, the Effective Pupil Lumens, the relative power level for equal pupil sizes, and a calculation of the Effective Pupil Lumens per watt. Table 1 Lumen Ratings of Selected Fluorescent Lamps... ..."

TABLE 2. Sequence of the fluorescence-labeled probesa

in unknown title
by unknown authors 1995

Table 1. Fluorescent probes used in these studies.

in Correspondence should be sent to:
by Kenneth W. Dunn, Ruben M. S, Katherine J. Kelly, Pierre C. Dagher, George A. Tanner, Simon J. Atkinson, Robert L. Bacallao, Bruce A. Molitoris, Kenneth Dunn
"... In PAGE 6: ...ver approximately 3 minutes. The total volume injected into mice was approximately 0.2 ml. The probes used in this study are summarized in Table1 , which also lists the amounts injected for each probe. Except as noted, imaging commenced within 5 minutes of injection.... ..."

Table 2 Results of color constancy algorithms applied to four images. The canonical illuminant was a Philips CW fluorescent light. The values shown are the RMS (over all pixels) magnitude of the chromaticity vector difference between the estimate and the desired answer, which is a view of the scene under the canonical light.

in Color constancy for scenes with varying illumination
by Kobus Barnard, Graham Finlayson, Brian Funt 1997
"... In PAGE 21: ... The printer is not calibrated so the images gives only rough qualitative result. Quantitative results can be found in Table2 . In the recovered versus canonical images, the green, yellow, blue and grey patches are much closer in colour than they are in the input versus the canonical.... In PAGE 22: ... Figure 4 shows the constraint sets generated for the input image in Figure 3. Table2 provides numerical results for three other scenes not shown in the Figures. One is a simple two-dimensional Mondrian made by attaching eight sheets of coloured construction paper to the lab wall such that substantial parts of the wall remained visible.... In PAGE 22: ... The cloth ball is interesting because the cloth has more texture than the construction paper. The numerical results in Table2 reflect the RMS difference (over the entire image) between the [r/b, g/b] chromaticities at corresponding pixels in the recovered and canonical images. There are few colour constancy algorithms designed to deal with scenes of the generality addressed here so it is difficult to make comparisons with existing algorithms without violating their assumptions.... In PAGE 22: ...26. Table2 also shows the chromaticity error for the case of doing nothing at all. The grey world algorithm, which uses the average image chromaticity as an illumination estimate, and the Retinex normalization strategy of taking the... ..."
Cited by 22

Table 1: Measurements for different renderings.

in ABSTRACT A New Object-Order Ray-Casting Algorithm
by Benjamin Mora, Jean-pierre Jessel, René Caubet

Table 2. The most similar five textures. Texture Texture Distance Texture Distance Texture Distance Texture Distance Texture Distance

in Set of Texture Similarity Measures
by Abdurrahman Carkacioglu, Abdurrahman Çarkacıoğlu A, Fatos Yarman-Vural
"... In PAGE 7: ... Experimental results show that MCL is very successful for identifying visually similar textures. Table2 shows the most similar five textures according to the Euclidean distance of Mean Clique Lengths. Visual inspection of the textures1- 35 and the quantitative analysis of table 2 indicate that the proposed distance is highly consistent with our human visual system in measuring the texture similarity.... ..."

Table 1. Platelet cholesterol and cholestatrienol fluorescence following treatment with bovine serum albumin Platelet [cholesterol] Fluorescence Treatment (molmol-1 Pi) Total fluorescence after TNBS Percentage quenched

in Collagen-Stimulated Unidirectional Translocation of Cholesterol in Human Platelet Membranes
by Kathleen Boesze-Battaglia, Richard J. Schimmel, Cholesterol In, Human Platelet Membranes
"... In PAGE 4: ...rom the inner to the outer monolayer; i.e. in the opposite direction. To detect reverse cholesterol translocation from the inner to the outer monolayer, platelets were labeled with C-3 as described above and then incubated with fatty-acid-free bovine serum albumin to remove the fluorescent sterol from the outer monolayer (see Table1 ). When albumin-treated platelets were reincubated, the percentage of TNBS- quenchable fluorescence gradually increased from less than 10 % to more than 50 % after 30 min of incubation (Fig.... ..."

Table 1 Feature sets defined for 2-D fluorescence microscope images.

in Journal of Biomedical Optics 9(5), 893–912 (September/October 2004) From quantitative microscopy to automated image understanding
by Kai Huang, Robert F. Murphy
"... In PAGE 3: ...et. For instance, SLF1.7, which is the variance of object dis- tances from the center of fluorescence, is the seventh feature in feature set SLF1. Table1 gives a summary of all current 2-D features grouped by various feature sets. The features derived from a parallel DNA channel for a target protein are included in the feature sets SLF2, SLF4, SLF5, and SLF13.... ..."
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