Sentence examples for merge approaches from inspiring English sources

In split and merge approaches, the input image is first sub-divided into a set of homogeneous primitive regions.

The existing techniques can be categorized into four classes ([6]): edge-based approaches, clustering-based approaches, region-based approaches, and split and merge approaches.

This paper has introduced a split and merge approach for image segmentation that aims to detect defects on fruit peel.

For image segmentation, split and merge approach is an efficient approach to employ local and global characteristics of color intensities of an image.

In this paper, a hybrid algorithm, which is based on split and merge approach, is proposed for an image segmentation that can be used in fruit defect detection.

In this paper, based on split and merge approach, we proposed a new hybrid algorithm that uses k-means clustering and Graph-based technique for splitting and merging image regions to segment fruit images.

We evaluated our approach using seven open source systems and compared it with different existing model merging approaches.

The new algorithms are compared against the best existing cluster ensemble merging approaches, clustering all the data at once and a clustering algorithm designed for very large data sets.

To this end, we first establish a high-density genetic linkage map by merging three existing SNP-based maps [ 31] using map merging approaches implemented in the software LPmerge [ 32, 33] and MergeMap [ 34].

The potential of merging approaches from different disciplines has been named before by Peacock et al., who proposed a novel interdisciplinary framework combining MCDA, A4R, Participatory Action Research (PAR) and Programme Budgeting and Marginal Analysis (PMBA) [ 59].

This paper considers the stream merging approach.