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In this paper, we introduce a novel discriminative loss function with large margin in the context of Deep Learning. This loss boosts the discriminative power of neural nets, represented by intra-class compactness and inter-class separability.
May 28, 2024
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Such g is sometimes called a discriminant function. For a fixed w, g(x; w) partitions the input space into two sets of regions, depending on whether g(x; w) ...
Missing: Discriminative | Show results with:Discriminative
May 29, 2024 · This paper introduces a new loss function called the "Large Margin Discriminative Loss" (LMDL) for training classification models.
Dec 15, 2023 · Instance segmentation using a discriminative loss? Ask Question ... I think the loss function is actually classifying the instances ...
Thus, the proposed regularization pushes a classifier toward the super-symmetric one while enlarging classifier margins as well as encouraging discriminative ...
Extensive experiments on four benchmark datasets demonstrate that the deeply-learned features with L-softmax loss become more discriminative, hence ...
The CLs feed a large-margin discriminant that, in turn, provides information to update the CLs' weights and increase the decision margin. A novel loss function ...
Missing: Discriminative | Show results with:Discriminative
However, this function can suffer from limitations on discriminative power, lack of generalization, and propensity to overfitting. In order to address these ...
In this work, we propose a novel sequence-discriminative training criterion for automatic speech recognition (ASR) based on the Conformer Transducer.
In this paper, we introduce a novel discriminative loss function with large margin in the context of Deep Learning. This loss boosts the discriminative power of ...