AI Medical Compendium Journal:
Neural networks : the official journal of the International Neural Network Society

Showing 21 to 30 of 2842 articles

Multi-level semantic-aware transformer for image captioning.

Neural networks : the official journal of the International Neural Network Society
Effective visual representation is crucial for image captioning task. Among the existing methods, the grid-based visual encoding methods take fragmented features extracted from the entire image as input, lacking the fine-grained semantic information ...

Enhancing text-centric fake news detection via external knowledge distillation from LLMs.

Neural networks : the official journal of the International Neural Network Society
Fake news poses a significant threat to society, making the automatic and accurate detection of fake news an urgent task. Various detection cues have been explored in extensive research, with news text content shown to be indispensable as it directly...

Deformation-invariant neural network and its applications in distorted image restoration and analysis.

Neural networks : the official journal of the International Neural Network Society
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...

A novel self-supervised graph clustering method with reliable semi-supervision.

Neural networks : the official journal of the International Neural Network Society
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...

Improving generalization of neural Vehicle Routing Problem solvers through the lens of model architecture.

Neural networks : the official journal of the International Neural Network Society
Neural models produce promising results when solving Vehicle Routing Problems (VRPs), but may often fall short in generalization. Recent attempts to enhance model generalization often incur unnecessarily large training cost or cannot be directly appl...

Bilinear Spatiotemporal Fusion Network: An efficient approach for traffic flow prediction.

Neural networks : the official journal of the International Neural Network Society
Accurate traffic flow forecasting is critical for intelligent transportation systems, yet increasing model complexity in spatiotemporal graph neural networks does not always yield proportional gains. In this paper, we present a Bilinear Spatiotempora...

A novel deep transfer learning method based on explainable feature extraction and domain reconstruction.

Neural networks : the official journal of the International Neural Network Society
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...

LUNETR: Language-Infused UNETR for precise pancreatic tumor segmentation in 3D medical image.

Neural networks : the official journal of the International Neural Network Society
The identification of early micro-lesions and adjacent blood vessels in CT scans plays a pivotal role in the clinical diagnosis of pancreatic cancer, considering its aggressive nature and high fatality rate. Despite the widespread application of deep...

EBM-WGF: Training energy-based models with Wasserstein gradient flow.

Neural networks : the official journal of the International Neural Network Society
Energy-based models (EBMs) show their efficiency in density estimation. However, MCMC sampling in traditional EBMs suffers from expensive computation. Although EBMs with minimax game avoid the above drawback, the energy estimation and generator's opt...

CFI-Former: Efficient lane detection by multi-granularity perceptual query attention transformer.

Neural networks : the official journal of the International Neural Network Society
Benefiting from the booming development of Transformer methods, the performance of lane detection tasks has been rapidly improved. However, due to the influence of inaccurate lane line shape constraints, the query sequences of existing transformer-ba...