Sentence examples for classification implemented from inspiring English sources
The CCBHNC uses a three-dimensional architecture with pixel classification implemented on its third dimension.
The designing process focuses on feature selection for pair-wise classification implemented by the SVM.
Secondly, according to the case study selected in this paper, the ground objects in the earthquake-stricken area are classified as bare areas, collapsed buildings, parallel buildings, and oriented buildings, using the Wishart supervised classification implemented on the PolSAR data after PolSAR compensation.
Given that resources for a repeat survey were limited, this study has used an object-orientated rule-based classification implemented within eCognition of multi-temporal satellite sensor data acquired between 2003 and 2006 to map semi-natural habitats and agricultural land across Wales, thereby allowing a progressive update of the Phase 1 Survey.
Starting with the MicroCyc or KEGG data, the user can choose from two up to fifteen organisms and select a subset or all the metabolic pathways from the classification implemented in KEGG or MetaCyc (39) (top of Figure 2D).
Remarkably, using the non-redundant functional classification implemented in MapMan software we were able to identify several pathways that showed coordinated changes in gene expression that was restricted to only one of the parental genomes.
The classification implements the fact that each subset acquires some new attribute for which all the previous attributes are needed.
This classification implements simpler criteria for grading erosive wear than the Lussi Index and it seems to be simple, fast and standardised tool suitable for monitoring erosion activities such as progression or arrest of lesions in competitive swimmers group.
When performing the classification analysis, we applied the medium classification stringency, implemented Benjamini multiple testing correction and set the threshold value of Enrichment score at 1.0 [ 34].
To gain insight into the predicted functional characteristics of the current dataset, translated products were functionally annotated using the Gene Ontology (GO) classification as implemented in the Blast2GO software [ 34], as well as using the InterPro classification [ 35].
The dynamical classification scheme implemented by the network eliminates all comparisons, which are the vital steps of the conventional nearest neighbor classification process.
