AIMC Topic: Neural Networks, Computer

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Siamese based deep neural network for ADHD detection using EEG signal.

Computers in biology and medicine
BACKGROUND: Detecting Attention-Deficit/Hyperactivity Disorder (ADHD) in children is crucial for timely intervention and personalized treatment.

A Multi-Scale Liver Tumor Segmentation Method Based on Residual and Hybrid Attention Enhanced Network with Contextual Integration.

Sensors (Basel, Switzerland)
Liver cancer is one of the malignancies with high mortality rates worldwide, and its timely detection and accurate diagnosis are crucial for improving patient prognosis. To address the limitations of traditional image segmentation techniques and the ...

Fed-CL- an atrial fibrillation prediction system using ECG signals employing federated learning mechanism.

Scientific reports
Deep learning has shown great promise in predicting Atrial Fibrillation using ECG signals and other vital signs. However, a major hurdle lies in the privacy concerns surrounding these datasets, which often contain sensitive patient information. Balan...

Bridging auditory perception and natural language processing with semantically informed deep neural networks.

Scientific reports
Sound recognition is effortless for humans but poses a significant challenge for artificial hearing systems. Deep neural networks (DNNs), especially convolutional neural networks (CNNs), have recently surpassed traditional machine learning in sound c...

Enhancing early Parkinson's disease detection through multimodal deep learning and explainable AI: insights from the PPMI database.

Scientific reports
Parkinson's is the second most common neurodegenerative disease, affecting nearly 8.5M people and steadily increasing. In this research, Multimodal Deep Learning is investigated for the Prodromal stage detection of Parkinson's Disease (PD), combining...

Smartphone region-wise image indoor localization using deep learning for indoor tourist attraction.

PloS one
Smart indoor tourist attractions, such as smart museums and aquariums, require a significant investment in indoor localization devices. The use of Global Positioning Systems on smartphones is unsuitable for scenarios where dense materials such as con...

Intermediate-grained kernel elements pruning with structured sparsity.

Neural networks : the official journal of the International Neural Network Society
Neural network pruning provides a promising prospect for the deployment of neural networks on embedded or mobile devices with limited resources. Although current structured strategies are unconstrained by specific hardware architecture in the phase o...

BGAT-CCRF: A novel end-to-end model for knowledge graph noise correction.

Neural networks : the official journal of the International Neural Network Society
Knowledge graph (KG) noise correction aims to select suitable candidates to correct the noises in KGs. Most of the existing studies have limited performance in repairing the noisy triple that contains more than one incorrect entity or relation, which...

Exploring refined dual visual features cross-combination for image captioning.

Neural networks : the official journal of the International Neural Network Society
For current image caption tasks used to encode region features and grid features Transformer-based encoders have become commonplace, because of their multi-head self-attention mechanism, the encoder can better capture the relationship between differe...

Multistability and fixed-time multisynchronization of switched neural networks with state-dependent switching rules.

Neural networks : the official journal of the International Neural Network Society
This paper presents theoretical results on the multistability and fixed-time synchronization of switched neural networks with multiple almost-periodic solutions and state-dependent switching rules. It is shown herein that the number, location, and st...