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Although the detection performance of this strong classifier is high, its training time is exceedingly long because of the large number of Haar-like features that needs to be trained for the weak classifiers.
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Key features that need to be included in non-adiabatic simulations are finally stressed out.
There are lots of natural places and landscape features that need protection.
There is a variety of features that need to be taken into account to choose the right software tool.
Building such models involves a multitude of decisions, and the large number of features that need to be taken into account can overwhelm the researcher.
Based on these experiences, we have identified three key features that need to be enhanced: heterogeneous IP import, orthogonalization of performance from behavior, and design space exploration.
However, shrinking a material to the nanoscale introduces new features that need to be taken into consideration when toxicity testing is conducted.
In this paper, we propose several major design features that need to be incorporated into large-scale optimization benchmark suites in order to better resemble the features of real-world problems.
There are two key features that need to be considered.
ProductBoard, however, is designed specifically for organizing, aggregating and prioritizing a long list of features that need to be built.
Correlation-based feature selection is an automatic algorithm, which does not need user-defined parameters like the number of features that need to be selected.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com