Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Heatmap-based anatomical landmark detection is still facing two unresolved challenges: (1) inability to accurately evaluate the distribution of heatmap; (2) inability to effectively exploit global spatial structure information. To address the computa...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Anomaly detection in the Industrial Internet of Things (IIoT) aims at identifying abnormal sensor signals to ensure industrial production safety. However, most existing models only focus on high accuracy by building a bulky neural network with deep s...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Zeroing neural networks (ZNNs) are commonly used for dynamic matrix equations, but their performance under numerically unstable conditions has not been thoroughly explored, especially in situations involving unequal row-column matrices. The challenge...
International journal of medical informatics
Jul 1, 2025
BACKGROUND: Hip fractures are associated with reduced mobility, and higher morbidity, mortality, and healthcare costs. Approximately 90% of hip fractures in the elderly are associated with osteoporosis, making it particularly important to screen the ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Existing neural network models to learn Hamiltonian systems, such as SympNets, although accurate in low-dimensions, struggle to learn the correct dynamics for high-dimensional many-body systems. Herein, we introduce Symplectic Graph Neural Networks (...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Although deep transfer learning has made significant progress, its "black-box" nature and unstable feature adaptation remain key obstacles. This study proposes a multi-stage deep transfer learning method, called XDTL, which combines explainable featu...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Directed graph neural networks (DGNNs) have garnered increasing interest, yet few studies have focused on node-level representation in directed graphs. In this paper, we argue that different nodes rely on neighbor information from different direction...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Images degraded by geometric distortions pose a significant challenge to imaging and computer vision tasks such as object recognition. Deep learning-based imaging models usually fail to give accurate performance for geometrically distorted images. In...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
3D anomaly detection aims to solve the problem that image anomaly detection is greatly affected by lighting conditions. As commercial confidentiality and personal privacy become increasingly paramount, access to training samples is often restricted. ...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Cluster analysis, as a core technique in unsupervised learning, has widespread applications. With the increasing complexity of data, deep clustering, which integrates the advantages of deep learning and traditional clustering algorithms, demonstrates...