Since is cone, we can select a sequence with such that for every.
Subsequently, in order to generate the non-cone set, we randomly selected a single point from each Voronoi edge for all training images, rounded to the nearest pixel value, and then extracted a 33 × 33 pixel patch around this location (Fig. 3(c)).
Select enough pine cones to make a rounded heap in a pie pan.
Thus, we devised a simple technique using Voronoi diagrams33 to select the non-cone locations.
For modeling spectral sensitivity, we selected the cone interaction that (1) included the minimum possible number of cones, (2) allowed for the best fit under all background conditions, and (3) ensured the same type of cone interaction (opponent and nonopponent) under all background conditions.
A point on a cone is selected manually, and the cone is tracked from frame to frame.
For each RGC, each selected cone was presented with an increment or decrement of light alone, and then separately paired with an increment of light to three other cones.
The selected volumes, after cone identification and volume registration, represented a time series, in which single cones could be monitored over time.
As an example, a point on a cone has been selected by mouse click on the image, and the cone has been tracked from frame to frame.
Quantification of β1-integrin clustering for quality control analysis was performed by randomly selecting growth cones (n = 50) for reevaluation with a range of fluorescence threshold values (two-, two and a half-, three-, and four-fold above the background fluorescence) [ 84].
