The phrase "a classification of local" is not complete and lacks context, making it difficult to determine its correctness in written English.
It could be used in contexts discussing categories or types of local entities, such as businesses, species, or events.
Example: "The study provides a classification of local species found in the region."
Alternatives: "a categorization of local" or "a grouping of local".
In this paper we contrast a static and a dynamic-based classification of local administrative units (LAU) in the Lisbon Metropolitan Area LMAA) to gain further insights onto the current land cover patterns and recent land cover changes in urban and peri-urban areas of the LMA.
A problem of classification of local field potentials (LFPs), recorded from the prefrontal cortex of a macaque monkey, is considered.
Theoretically, the paper provides an institutionally oriented classification of local electricity initiatives, based on coordination, technology and performance.
Finally, we apply this computer vision-based approach for the unsupervised detection and classification of local structural states in an experimental electron micrograph of a complex oxides interface, and a scanning tunneling micrograph of a defect-engineered multilayer graphene surface.
In the proposed system, we use a support vector machine (SVM) [40] for the classification of local features.
Because we investigate transient behavior originating from a high threshold regime (toward weak excitability), the classification of local excitability in types I and II (based on the transition at vanishing threshold, i.e., into the oscillatory regime) is not relevant.
Fig. 3 Classification of Local Structural States.
This method is based on classification of local image patterns using both structure information and activity measure to explicitly distinguish pixels into content or coding artifacts.
Finally, we conclude by demonstrating automated extraction and classification of local structural states in STEM images of strained interfaces of SrTiO3/LaCoO3 and local modulations in the electron density of states near defects on graphite surfaces imaged by scanning tunneling microscopy.
The mean accuracy of the methods for classification of local data varied from 0.78 to 0.87, which as expected was less than that for the PPMI data where mean accuracies varied between 0.89 and 0.95.
