Sentence examples for resource classification from inspiring English sources

The SPE/WPC/AAPG resource classification system provides an ideal basis for this approach.

G-Portal also includes a resource classification module that categorizes resources into one or more hierarchical category trees based on user-defined classification schemas.

To arrive at the "ten times" statistic, the team used industry-standard "linguistic resource classification," which is to say that it scanned for the frequency of words such as "excessive," "miss," "wrong," "ridiculous," "wasted," "degrading," "evil," "crap," and "ugly" versus "yay," "best," "love," "happy," "great," "amazing," "beautiful," "like," "you rock!," and "heartwarming".

Resource classification in categories existing in all repositories was automatically evaluated, obtaining maximum performance values of 84% (F1 score), 87.8% (area under the receiver operator characteristic curve), 86% (area under the precision-recall curve) and 75.1% (Cohen's κ).

These results demonstrate the potential of this approach as a tool to facilitate resource classification, for example to provide a preliminary classification that would require just minor corrections from human classifiers.

However, based on SWERA wind resource classification scheme, it can be concluded that wind resources in all selected locations are falling into class 1 (poor).

Image segmentation is a popular research topic in image processing, as it has a number of significant applications in object detection and moving object tracking, resources classification in SAR images, organs segmentation and 3D reconstruction in medical images, etc.

In the global South countless informal and organized solid waste collectors are engaged in resource recovery, classification of discarded waste, and redirection of recyclables towards the recycling sector.

Note that the accuracy increases as we test a more specific subset of resource name classifications, showing that the filtering steps we used during network generation removed the majority of the incorrectly categorized instances.

It can help in water resource management, catchment classification, and prediction of runoff time series.

Despite its classroom schedule, Wise refers to itself as a "learning-based resource center". This classification allows California STEAM Sonoma to sponsor the program, and the Liberty School District to acquire the cash cow.