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The proposed DFBP and Verif.-Identif [16] utilize the verification and identification models.
Experiments are performed both in verification and identification modes.
The correct verification and identification for long hair may be difficult to fulfil.
Suitable approaches for the verification and identification scenarios can be different in principle.
Verification and identification experiments were conducted in order to evaluate the performance of the proposed method.
Feature compensation (normalization) is widely and effectively used for speaker verification and identification tasks.
Similar(27)
There are mainly two kinds of CNN models, i.e., verification models and identification models.
There are two major kinds of CNN models for person re-identification, i.e., verification network and identification network.
In the learning process, we simultaneously utilize two kinds of models, i.e., verification models and identification models, to learn and extract features.
The two methods both utilize the verification network and identification network to learn the features, while the proposed LEDF explicitly considers the structural information of pedestrian.
A similar idea, also working on the signal wavelet domain, has been applied to audio in [5], with the aim of copyright verification and tampering identification.
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