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In the first part of this paper, we describe the data representation.
The former method is fast to sample, yet sacrifices the accuracy of the data representation.
The data representation based on an iris-code offers compact storage and rapid Hamming distance-based (H D) comparison.
In our example, the performance improvement would not have been possible without the proper selection of the data representation model.
Given the number of bits of the data representation, digital platforms guarantee accuracy independently of the technology process.
Therefore, the system engineers and architects must give enough consideration to the selection of the data representation model.
Similar(11)
The data representations describe the design of transit data models.
We outline and discuss the diverse available options in optimizing the data representations used.
The data representations in the hidden layer present meaningful abstraction levels for the analysis of the learning performed.
Earlier, we discussed some studies that utilize the data representations extracted through Deep Learning for semantic indexing.
But (ON), and hence GDI, does not specify whether, ultimately, the occurrence of every discrete state necessarily requires a material implementation of the data representations.
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