Heterogeneous data captured by different scanning devices and imaging protocols can affect the generalization performance of the deep learning magnetic resonance (MR) reconstruction model. While a centralized training model is effective in mitigating...
Traditional DNA storage technologies rely on passive filtering methods for error correction during synthesis and sequencing, which result in redundancy and inadequate error correction. Addressing this, the Low Quality Sequence Filter (LQSF) was intro...
Neural networks : the official journal of the International Neural Network Society
Jan 1, 2025
This work concentrates on solving the finite-time H output synchronization (FTHOS) issue of directed coupled reaction-diffusion neural networks (DCRDNNs) with multiple delayed and adaptive output couplings in the presence of external disturbances. Ba...
Neural networks : the official journal of the International Neural Network Society
Jan 1, 2025
In the domain of online reinforcement learning, strategies that leverage inherent rewards for exploration tend to achieve commendable outcomes within contexts characterized by deceptive or sparse rewards. Counting through the visitation of states is ...
Neural networks : the official journal of the International Neural Network Society
Jan 1, 2025
Graph Neural Networks (GNNs) have shown remarkable achievements and have been extensively applied in various downstream tasks, such as node classification and community detection. However, recent studies have demonstrated that GNNs are vulnerable to ...
Neural networks : the official journal of the International Neural Network Society
Jan 1, 2025
Spiking Neural Networks (SNNs) are at the forefront of computational neuroscience, emulating the nuanced dynamics of biological systems. In the realm of SNN training methods, the conversion from ANNs to SNNs has generated significant interest due to ...
Recent advancements in cardiac imaging have been significantly enhanced by integrating deep learning models, offering transformative potential in early diagnosis and patient care. The research paper explores the application of hybrid deep learning me...
Early diagnosis of neurodegenerative diseases, such as Alzheimer's disease, improves treatment and care outcomes for patients. Early signs of cognitive decline can be detected using functional scales, which are written records completed by a clinicia...
BACKGROUND: To address critical security challenges in the Internet of Medical Things (IoMT), this study develops a feature selection framework to improve detection accuracy and computational efficiency in IoMT cybersecurity. By optimizing feature se...
This article revisits Artificial Neural Networks (NNs) through the lens of Evolutionary Dynamics. The two most important features of NNs are shown to reflect the two most general processes of Evolutionary Dynamics. This overlap may serve as a new and...
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