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Representation of features is an important aspect for making feature recognition more applicable in practice.
To achieve this, we generate conservation targets at landscape scales rather than focusing purely on the representation of features within reserves.
Fuzzy logic naturally models human logic allowing for the nuanced representation of features of objects and thus is utilized to derive such gradual representation as well as for modeling user profiles.
This possibility raises a fundamental problem for conservation biology: conservation planning must have as its goal the future representation of features, not merely their present representation in CANs.
In this paper, we propose a novel scheme for palmprint recognition using a sparse representation of features obtained from Bank of Binarized Statistical Image Features (B-BSIF).
Thus, the sparse representation of features obtained from each filter in the B-BSIF can be carried out as follows: 1.
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Here we review results of experiments that challenge the place code model for the representation of feature combinations.
Experiments 1 and 2 were motivated by the hypothesis that the internal generation and representation of feature templates (object files) is the engaging factor in WM performance.
In healthy vision, crowding has been interpreted as a pre-attentive process that uses averaging to regularize the noisy representation of (feature) position in the periphery (Greenwood et al., 2009).
Traditional SLAM solutions tend to use a robot's sensors to continuously construct geometric maps of its surroundings or to create symbolic representations of features around the robot.
Geographic information is commonly disseminated and consumed via visual representations of features and their environmental context on maps.
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