نتایج جستجو برای: foreground selection
تعداد نتایج: 323903 فیلتر نتایج به سال:
for manipulating QTL in foreground selection. Further, they investigated the combination of foreground and Marker-assisted selection can accelerate recovery of the recurrent background selection in QTL introgression. Openshaw parent genome (RPG) in backcross breeding. In this study, we used et al. (1994) determined the population size and marker computer simulations to compare selection strateg...
Business Process Management (BPM) tool, which will be used in the management, improvement and maintenance of business processes, continues to increase its importance in the enterprise software projects where business processes are involved. In enterprise software projects, many criteria are in the foreground in the selection of BPM tool. These criteria are shaped by the requirements and the tec...
Label-equivalence-based connected-component labeling algorithms complete labeling in two or more raster scans. In the first scan, each foreground pixel is assigned a provisional label, and label equivalences between provisional labels are recorded. For doing this task, all conventional algorithms use the same mask that consists of four processed neighbor pixels to process every foreground pixel...
The effects of a foreground stimulus on vection (illusory perception of self-motion induced by a moving background stimulus) were examined in two experiments. The experiments reveal that the presentation of a foreground pattern with a moving background stimulus may affect vection. The foreground stimulus facilitated vection strength when it remained stationary or moved slowly in the opposite di...
We present a new estimate of foreground emission in the WMAP data, using a Markov chain Monte Carlo (MCMC) method. The new technique delivers maps of each foreground component for a variety of foreground models with estimates
We propose a region-based method to extract foreground regions from colour video sequences. The foreground region is decided by voting with scores from background subtraction to the sub-regions by graphbased segmentation. Experiments show that the proposed algorithm improves on conventional approaches especially in strong shadow regions.
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