Sentence examples for constrained classification from inspiring English sources

Multiple methods exist for boundary delineation such as two-dimensional wombling, constrained classification techniques and discontinuity detection.

Seven methods designed to delineate homogeneous river segments, belonging to four families, namely — tests of homogeneity, contrast enhancing, spatially constrained classification, and hidden Markov models — are compared, firstly on their principles, then on a case study, and on theoretical templates.

Constrained based classification and spectral clustering are then applied on the selected features to categorize the road-users.

In contrast to conventional (static), data-driven multi-class machine learning (ML), we exploit process knowledge in order to constrain our classification system yielding more parsimonious models compared to static ML approaches.

However, over and above basic tallies, the usefulness of these descriptive data for epidemiological research is constrained by the classification system applied, which for haematological malignancies is largely rooted in the gradual recognition of disease entities at the beginning of the twentieth century.

The selection of a machine learning method for sign classification is constrained to the choice of features.

In brain tumor segmentation, the methods based on pixel classification are constrained to the use of supervised or unsupervised classifiers to cluster pixels in the feature space.

The forest is intended to be a representative sample of classification trees constrained so that trees more consistent with prior information are more heavily represented.

LLDE apply the constrained weights to strengthen the classification ability.

At the root of the success of kernel-based learning, the combination of high expressive power with the possibility to perform the numerous analyses has been developed in many challenging applications [65], e.g., online classification [66], convexly constrained parameter/function estimation [67], beamforming problems [68], and adaptive multiregression [69].

However, different indices increased the computational cost and constrained the satellite data sources, and the traditional classification methods (e.g. Maximum Likelihood Classification) could be a time-consuming process and difficult to carry out over a large area like China.