Traditional object definition

Traditional object means any object or item deemed by the affiliated tribe to be integral to its customs and traditions.”
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Examples of Traditional object in a sentence

  • Traditional object storage uses one capability to authorize access to each object.

  • Traditional object detection and tracking algorithms, which are also computationally expensive for a large number of objects, often fail in the case of severe occlusions [1].

  • Traditional object recognition methods are trained on large datasets where the true bounding boxes are annotated, data which is not freely available in many domains, including ours.

  • Traditional object detection and localization approaches in DCNNs are mainly based on classification and regression[35].

  • It is even conceivable to have this combination on one platform.- Traditional object recognition approaches must be extended to include classification techniques that have been successfully used in remote sensing for many years.

  • Traditional object proximity models measure the total strength of various interactions by counting the number of instances ofdifferent meta-paths between objects and adding up the counts with pre-defined or learned weights [18], [23], [19], [37], [22], [21], [38], [14], [39], whereas the more recent network representation learning methods leverage meta-path guided random walks to jointly model multiple interactions in a latent embedding space [20], [40], [15], [41], [13], [42].

  • Traditional object- oriented approaches offer no support to combine several ob- jects to an entity, without loosing the decomposition.

  • Traditional object cloning techniques produce clones using either shallow cloning or deep cloning.

  • Traditional object technologies, with their emphasis on iterative development, allow the construction of reusable assets in a bottom-up fashion.

  • Object detection Object detection is a computer vision technology which uses algorithms to search for objects of interest in images.[6] Traditional object detection included preprocessing, window sliding, feature extraction, feature selection, classification, post-processing and so on.[7] The traditional fea- ture extraction had poor generalization ability and low accuracy.

Related to Traditional object

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