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The accuracy of the scenes registration in the proposed framework has been tested with the common datasets prepared by (Sturm et al. 2012) in the Computer Vision Groups at the Technische Universität München.
The scientific motivations for sharing these data are compelling: common datasets can provide meaningful comparisons between competing research approaches; simulated data are inadequate for some uses; and existing datasets may not reflect present-day threats or traffic characteristics [31].
We extracted some versions from randomly chosen links to common datasets in the linked open data (LOD) cloud [22], such as Dbpedia and DBPL, as well as FOAF Profiles.
The availability of common datasets is important to the scientific community.
In these cases, having common datasets to work with becomes critical.
A deficiency in the field has been the lack of common datasets for researchers to test their algorithms on.
Similar(40)
A total of 15 algorithms were submitted and evaluated under a common dataset.
An evaluation of different face recognition algorithms using a common dataset has been of general interest.
The various map sheets obtained were processed and merged together to a common dataset.
In this context, we assess the logit and signal extraction EWS for banking crises on a comprehensive common dataset.
The most common dataset is the updated version of atmPrf products published by CDAAC, which is known as 2013.3520.
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