AIMC Topic: Fourier Analysis

Clear Filters Showing 11 to 20 of 143 articles

Multi-modal signal integration for enhanced sleep stage classification: Leveraging EOG and 2-channel EEG data with advanced feature extraction.

Artificial intelligence in medicine
This paper introduces an innovative approach to sleep stage classification, leveraging a multi-modal signal integration framework encompassing Electrooculography (EOG) and two-channel electroencephalography (EEG) data. We explore the utility of vario...

Tiny Convolutional Neural Network with Supervised Contrastive Learning for Epileptic Seizure Prediction.

International journal of neural systems
Automatic seizure prediction based on ElectroEncephaloGraphy (EEG) ensures the safety of patients with epilepsy and mitigates anxiety. In recent years, significant progress has been made in this field. However, the predictive performance of existing ...

Complex-valued neural networks to speed-up MR thermometry during hyperthermia using Fourier PD and PDUNet.

Scientific reports
Hyperthermia (HT) in combination with radio- and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously heated to temperatures between 39 and 43 °C for 60 min. Temperature monit...

Deep learning-based prediction of atrial fibrillation from polar transformed time-frequency electrocardiogram.

PloS one
Portable and wearable electrocardiogram (ECG) devices are increasingly utilized in healthcare for monitoring heart rhythms and detecting cardiac arrhythmias or other heart conditions. The integration of ECG signal visualization with AI-based abnormal...

Radar Signal Processing and Its Impact on Deep Learning-Driven Human Activity Recognition.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) using radar technology is becoming increasingly valuable for applications in areas such as smart security systems, healthcare monitoring, and interactive computing. This study investigates the integration of convoluti...

When low-light meets flares: Towards Synchronous Flare Removal and Brightness Enhancement.

Neural networks : the official journal of the International Neural Network Society
Low-light image enhancement (LLIE) aims to improve the visibility and illumination of low-light images. However, real-world low-light images are usually accompanied with flares caused by light sources, which make it difficult to discern the content o...

Improved analysis of supervised learning in the RKHS with random features: Beyond least squares.

Neural networks : the official journal of the International Neural Network Society
We consider kernel-based supervised learning using random Fourier features, focusing on its statistical error bounds and generalization properties with general loss functions. Beyond the least squares loss, existing results only demonstrate worst-cas...

AutoSamp: Autoencoding k-Space Sampling via Variational Information Maximization for 3D MRI.

IEEE transactions on medical imaging
Accelerated MRI protocols routinely involve a predefined sampling pattern that undersamples the k-space. Finding an optimal pattern can enhance the reconstruction quality, however this optimization is a challenging task. To address this challenge, we...

A parallel CNN architecture for sport activity recognition based on minimal movement data.

Scientific reports
Novel Human Activity Recognition (HAR) methodologies, which are built upon learning algorithms and employ ubiquitous sensors, have achieved remarkable precision in the identification of sports activities. Such progress benefits all age groups of huma...

Fluorescence excitation-emission matrix spectroscopy combined with machine learning for the classification of viruses for respiratory infections.

Talanta
Significant efforts were currently being made worldwide to develop a tool capable of distinguishing between various harmful viruses through simple analysis. In this study, we utilized fluorescence excitation-emission matrix (EEM) spectroscopy as a ra...