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In the cross-domain detection experiment, our method has better robustness.
Applied to data from a bacterial evolution experiment, our method reproduces an observed correlation between evolvability and initial fitness defect.
Compared with the integrating method in Zhao et al., like the former experiment, our method has the same results but using less time.
For each experiment, our method outputs the gene pairs authorizing a functional transfer in an organized way, by presenting in cluster pairs the coexpressed genes whose coexpression has been conserved.
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We also experiment our methods on fingertip detection and human pose datasets and obtain state-of-the-art accuracy.
In all experiments our method demonstrates superior accuracy and robustness compared to prior arts.
In the experiments, our method consistently demonstrates high-quality image/video retexturing with real-time feedback interaction.
In the experiments, our method can process online video input captured by a 25-camera array and show the result image at 4.55 fps.
In extensive experiments, our method is shown to produce accurate models of indoor and outdoor environments that compare favorably to other methods.
We experimented our method on a set of real-world orchestrations (BPEL processes) to measure the overhead of using it in engineering such service-oriented applications.
As shown in our experiments, our method can be applied to datasets containing quite a large number of users (although it obviously is a difference between a few thousand users and "Web scale").
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