Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
The current few-shot relational triple extraction (FS-RTE) techniques, which rely on prototype networks, have made significant progress. Nevertheless, the scarcity of data in the support set results in both intra-class and inter-class gaps in FS-RTE....
Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
Reconstruction-based methods achieve promising performance for visual anomaly detection (AD), relying on the underlying assumption that the anomalies cannot be accurately reconstructed. However, this assumption does not always hold, especially when s...
Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
Unsupervised domain adaptation (UDA) aims to annotate unlabeled target domain samples using transferable knowledge learned from the labeled source domain. Optimal transport (OT) is a widely adopted probability metric in transfer learning for quantify...
Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
Sequential recommendation models aim to predict the next item based on the sequence of items users interact with, ordered chronologically. However, these models face the challenge of data sparsity. Recent studies have explored cross-domain sequential...
Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
Learning from data streams that emerge from nonstationary environments has many real-world applications and poses various challenges. A key characteristic of such a task is the varying nature of the underlying data distributions over time (concept dr...
Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
Shadow removal remains a challenging visual task aimed at restoring the original brightness of shadow regions in images. Many existing methods overlook the implicit clues within non-shadow regions, leading to inconsistencies in the color, texture, an...
Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
Model-based diagnosis (MBD) is a critical problem in artificial intelligence. Recent advancements have made it possible to address this challenge using methods like deep learning. However, current approaches that use deep learning for MBD often strug...
Neural networks : the official journal of the International Neural Network Society
Jan 22, 2025
Detecting anomalies in attributed networks has become a subject of interest in both academia and industry due to its wide spectrum of applications. Although most existing methods achieve desirable performance by the merit of various graph neural netw...
BACKGROUND: Multiple sclerosis (MS) is an autoimmune inflammatory disorder that causes neurological disability. Dysregulated lipid metabolism contributes to the pathogenesis of MS. This study aimed to identify lipid metabolism-related gene markers an...
Semi-supervised 3D medical image segmentation aims to achieve accurate segmentation using few labelled data and numerous unlabelled data. The main challenge in the design of semi-supervised learning methods consists in the effective use of the unlabe...
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