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

Showing 61 to 70 of 2842 articles

Neural networks trained by weight permutation are universal approximators.

Neural networks : the official journal of the International Neural Network Society
The universal approximation property is fundamental to the success of neural networks, and has traditionally been achieved by training networks without any constraints on their parameters. However, recent experimental research proposed a novel permut...

ADAMT: Adaptive distributed multi-task learning for efficient image recognition in Mobile Ad-hoc Networks.

Neural networks : the official journal of the International Neural Network Society
Distributed machine learning in mobile adhoc networks faces significant challenges due to the limited computational resources of devices, non-IID data distribution, and dynamic network topology. Existing approaches often rely on centralized coordinat...

HCPI-HRL: Human Causal Perception and Inference-driven Hierarchical Reinforcement Learning.

Neural networks : the official journal of the International Neural Network Society
The dependency on extensive expert knowledge for defining subgoals in hierarchical reinforcement learning (HRL) restricts the training efficiency and adaptability of HRL agents in complex, dynamic environments. Inspired by human-guided causal discove...

Deep Huber quantile regression networks.

Neural networks : the official journal of the International Neural Network Society
Typical machine learning regression applications aim to report the mean or the median of the predictive probability distribution, via training with a squared or an absolute error scoring function. The importance of issuing predictions of more functio...

Heterogeneous Graph Neural Network with Adaptive Relation Reconstruction.

Neural networks : the official journal of the International Neural Network Society
Topological structures of real-world graphs often exhibit heterogeneity involving diverse nodes and relation types. In recent years, heterogeneous graph learning methods utilizing meta-paths to capture composite relations and guide neighbor selection...

Revisiting face forgery detection towards generalization.

Neural networks : the official journal of the International Neural Network Society
Face forgery detection aims to distinguish AI generated fake faces with real faces. With the rapid development of face forgery creation algorithms, a large number of generative models have been proposed, which gradually reduce the local distortion ph...

Learn the global prompt in the low-rank tensor space for heterogeneous federated learning.

Neural networks : the official journal of the International Neural Network Society
Federated learning collaborates with multiple clients to train a global model, enhancing the model generalization while allowing the local data transmission-free and security. However, federated learning currently faces three intractable challenges: ...

Dual selective fusion transformer network for hyperspectral image classification.

Neural networks : the official journal of the International Neural Network Society
Transformer has achieved satisfactory results in the field of hyperspectral image (HSI) classification. However, existing Transformer models face two key challenges when dealing with HSI scenes characterized by diverse land cover types and rich spect...

Hy-DeFake: Hypergraph neural networks for detecting fake news in online social networks.

Neural networks : the official journal of the International Neural Network Society
Nowadays social media is the primary platform for people to obtain news and share information. Combating online fake news has become an urgent task to reduce the damage it causes to society. Existing methods typically improve their fake news detectio...

ABVS breast tumour segmentation via integrating CNN with dilated sampling self-attention and feature interaction Transformer.

Neural networks : the official journal of the International Neural Network Society
Given the rapid increase in breast cancer incidence, the Automated Breast Volume Scanner (ABVS) is developed to screen breast tumours efficiently and accurately. However, reviewing ABVS images is a challenging task owing to the significant variations...