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OU-ISIR Gait Database, Large Population Dataset with Age.
We focused on the OU-ISIR Gait Database, Large Population Dataset.
Fig. 1 Examples of captured images in the OU-ISIR Gait Database, Large Population Dataset.
We call this dataset the "OU-ISIR Gait Database, Large Population Dataset with Age" (OULP-Age)1.
The OU-ISIR Gait Database, Large Population Dataset [27] was collected with the aim to a statistically reliable performance evaluation of large-scale gait recognition.
Recently, a large dataset, the OU-ISIR Gait Database, Large Population Dataset with Bag, β version, which contains 2,070 subjects with various COs, was introduced in [22]; however, it does not include detailed information about COs.
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He noted that in the era of mass databases, large amounts of secret information are now stored on computers.
Moreover, the report found that the F.B.I. improperly uploaded into its databases large numbers of calling records without determining whether they were relevant to an investigation.
This chapter is an overview of architectural principles as they apply to databases and large databases in particular.
On the other hand, for large training databases, larger number of contextual regions has to be defined to escape from under-fitting model to training data.
The expected number of random matches (e-value) was kept under 1E-50 for individual TIGR databases larger databases (e.g. NCBI nr restricted to Fabaceae hits).
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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