Mar 7, 2019 · We propose a customized weighted discriminative loss (CWD loss) to seek a customized constraint for mitigating the large perturbations caused by imbalanced ...
To enhance the discrimination of deeply learned face features, we propose a customized weighted discriminative loss (CWD loss) to seek a customized constraint ...
Dec 19, 2018 · It focuses on mapping the raw data into a feature space such that deeply learned face features can achieve a high discrimination for ...
To enhance the discrimination of deeply learned face features, we propose a customized weighted discriminative loss (CWD loss) to seek a customized constraint ...
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Different convolutional neural networks (CNNs) may learn different levels of discriminative features to represent the raw face data.
Learning deep discriminative face features by customized weighted constraint ... Deep compact discriminative representation for unconstrained face recognition.
Learning deep discriminative face features by customized weighted constraint. ... Jointly learning perceptually heterogeneous features for blind 3D video ...
Jun 8, 2022 · Wu, “Learning deep discriminative face features by customised weighted constraint,” Neurocomputing, vol. 332, pp. 71–79, Mar. 2019. [5]D ...
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Specifically, the center loss simultaneously learns a center for deep features of each class and penalizes the distances between the deep features and their ...
The intra-class constraint is extended to force the intra- class cosine similarity larger than the mean of nearest neighboring inter-class ones with a ...