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Dynamic Stochastic Ensemble with Adversarial Robust Lottery Ticket Subnetworks
Adversarial attacks are considered the intrinsic vulnerability of CNNs.
An Improved Automatic Modulation Classification Scheme Based on Adaptive Fusion Network
Moreover, a novel confidence weighted loss function is proposed to address the imbalance issue and it is implemented by a two-stage learning scheme. Through the two-stage learning, AFNet can focus on high-confidence samples with more valid information and extract effective representations, so as to improve the overall classification performance.
Heterogeneous Architecture Search Approach within Adversarial Dynamic Defense Framework
Recent advances in adversarial attacks uncover the intrinsic vulnerability of modern deep neural networks (DNNs).
A density compensation-based path computing model for measuring semantic similarity
Therefore, in order to solve the problem of non-uniformity of concept density in a large taxonomic ontology, we propose a new path computing model based on the compensation of local area density of concepts, which is equal to the number of direct hyponyms of the subsumers of concepts in their shortest path.
