AIMC Topic: Neural Networks, Computer
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Dynamic cross-domain transfer learning for driver fatigue monitoring: multi-modal sensor fusion with adaptive real-time personalizations.
Scientific reports
May 6, 2025
Driver fatigue is one of the most common causes of road accidents, which means that there is a great need for robust and adaptive monitoring systems. Current models of fatigue detection suffer from domain-specific limitations in generalizing across d...
Novel approach for AI-based NO emission reduction in biological wastewater treatment relying on genetic algorithms and neural networks.
Water science and technology : a journal of the International Association on Water Pollution Research
May 6, 2025
The potential of measurement-based control strategies for achieving lower NO emissions in biological wastewater treatment is limited due to strong temporal variations in NO emissions and a lack of measurement data regarding influencing parameters. To...
Multiscale simulations that incorporate patient-specific neural network models of platelet calcium signaling predict diverse thrombotic outcomes under flow.
PLoS computational biology
May 6, 2025
During thrombosis, platelets rapidly deposit and activate on the vessel wall, driving conditions such as myocardial infarction and stroke. The complexity of thrombus formation in pathological flow geometries, along with patient-specific pharmacologic...
Multivariate Glucose Forecasting Using Deep Multihead Attention Layers Inside Neural Basis Expansion Networks.
IEEE journal of biomedical and health informatics
May 6, 2025
Glucose forecasting is a crucial feature in a closed-loop diabetes management system relying on minimally invasive continuous glucose monitoring (CGM) sensors. Forecasting is required to prevent hyperglycaemia or hypoglycaemia due to delayed or incor...
A Distributed Neural Network Architecture for Dynamic Sensor Selection With Application to Bandwidth-Constrained Body-Sensor Networks.
IEEE journal of biomedical and health informatics
May 6, 2025
We propose a dynamic sensor selection approach for deep neural networks (DNNs), which is able to derive an optimal sensor subset selection for each specific input sample instead of a fixed selection for the entire dataset. This dynamic selection is j...
MHFNet: A Multimodal Hybrid-Embedding Fusion Network for Automatic Sleep Staging.
IEEE journal of biomedical and health informatics
May 6, 2025
Scoring sleep stages is essential for evaluating the status of sleep continuity and comprehending its structure. Despite previous attempts, automating sleep scoring remains challenging. First, most existing works did not fuse local and global tempora...
MLDA-Net: Multi-Level Deep Aggregation Network for 3D Nuclei Instance Segmentation.
IEEE journal of biomedical and health informatics
May 6, 2025
Segmentation of cell nuclei from three-dimensional (3D) volumetric fluorescence microscopy images is crucial for biological and clinical analyses. In recent years, convolutional neural networks have become the reliable 3D medical image segmentation s...
FlexibleSleepNet:A Model for Automatic Sleep Stage Classification Based on Multi-Channel Polysomnography.
IEEE journal of biomedical and health informatics
May 6, 2025
In the task of automatic sleep stage classification, deep learning models often face the challenge of balancing temporal-spatial feature extraction with computational complexity. To address this issue, this study introduces FlexibleSleepNet, a lightw...
SWMA-UNet: Multi-Path Attention Network for Improved Medical Image Segmentation.
IEEE journal of biomedical and health informatics
May 6, 2025
In recent years, deep learning achieves significant advancements in medical image segmentation. Research finds that integrating Transformers and CNNs effectively addresses the limitations of CNNs in managing long-distance dependencies and understandi...
TCGAN: Temporal Convolutional Generative Adversarial Network for Fetal ECG Extraction Using Single-Channel Abdominal ECG.
IEEE journal of biomedical and health informatics
May 6, 2025
Noninvasive fetal ECG (FECG) monitoring holds significant importance in ensuring the normal development of the fetus. Since FECG is usually submerged by maternal ECG (MECG) and background noise in abdominal ECG (AECG), it is challenging to exactly re...
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