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The species was named as a separate subgenus of Peromyscus by Wilfred Hudson Osgood in 1909, but generic recognition was disputed in the 1980s.
Within the latter, no support is recovered for the generic recognition of Blanfordimys, Lasiopodomys, Neodon, and Phaiomys as suggested by morphology.
However, except for Chionomys (snow voles), other taxa are interspersed among "true" Microtus lineages in our nuclear or combined topologies, giving no support to their generic recognition.
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Generic object recognition requires models that cope with the diversity of instances' appearances and shapes.
Generic object recognition is to classify the object to a generic category.
However, it is desirable to evaluate the proposed method using the generic object recognition data set.
The above idea is inspired by the implicit shape model [19], which is used for generic object recognition.
The architecture is implemented using generic visual recognition techniques and commonsense reasoning to extract graphs from images.
Generic iris recognition systems, see Fig. 1 a, consist of four major modules: (1) image acquisition; (2) pre-processing; (3) feature extraction; and (4) comparison.
Applying our LG-CNN architecture to generic object recognition datasets also yields superior performance over the directly fine-tuned CNN architecture with a large margin.
Detection deals with the difficulties of generic object recognition, i.e., finding instances from a particular object class or semantic category (e.g., humans, faces, vehicles) registered in digital images and videos.
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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