To verify the pretreatment method, we compared the 3H concentration obtained by using silica gel with that obtained by lyophilization of four plant samples.
For further assessing the object-based method we compared its results with the results of pixel-based classification, using the same classifier.
In order to test our method, we compared it with other two traditional approaches, which consider structural and tree floristic variables separately.
To validate outcomes of this method, we compared microarray-derived inaccessibility scores to results of independent DNase I-PCR experiments without size fractionation for genomic fragments at two pericentromeric TE genes, two active genes and twelve fragments at genes of high inaccessibility (Supplementary Fig. S1).
In this method, we compared R-OSATS scores from "inexperienced" (34 postgraduate year 1 and 2 trainees) with "experienced" (22 faculty and fellow) robotic surgeons.
Therefore, as an alternative method, we compared the histogram of ground pulse intervals and those detected with the LIDAR.
To evaluate the proposed method, we compared the results with several state-of-the-art methods listed below.
In order to confirm the effectiveness of the our proposed method, we compared our method with RANSAC, Yu's method, and Shao's method for many simulation data.
In order to measure the error of our method, we compared the points of the detected boundaries with those of the real boundaries.
To measure the relative precision of the human-guided video processing method, we compared user-corrected trajectories against the ones extracted by a fully automated algorithm.
For the assessment of the effectiveness of this method, we compared radiographic parameters measured on initial postoperative radiographs with those of final radiographs.
