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By performing process planning with maximal features, the optimal or satisfactory feature interpretation will be found.
The results confirmed that the prototype was suitable for 3D spatial data capture and feature interpretation of crime suspects in court.
Precise preoperative anatomic localization and computed tomography and magnetic resonance imaging feature interpretation play a paramount role in achieving an accurate final diagnosis.
In this paper a hybrid procedural and knowledge-based approach based on artificial intelligence planning is presented, which addresses both classic feature interpretation and also feature representation problems.
In this study, feature selection is used mainly for the simplification of models for better feature interpretation, and for the reduction of overfitting.
We added the following explanation on this issue to Section "Feature interpretation and selection" in the Methods section.
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Multiple feature interpretations and lack of scalability have been issues in the latest feature recognition research.
The algorithm takes multiple feature interpretations of a part as input.
We present an algorithm that generates multiple feature interpretations within and across domains.
The algorithm generates multiple feature interpretations for parts, which have a through feature in any one domain.
We define three types of multiple feature interpretations or models, (1) only positive, (2) mixed and (3) only negative.
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