AIMC Topic: Fourier Analysis

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Automatic sleep stage classification: A light and efficient deep neural network model based on time, frequency and fractional Fourier transform domain features.

Artificial intelligence in medicine
This work proposed a novel method for automatic sleep stage classification based on the time, frequency, and fractional Fourier transform (FRFT) domain features extracted from a single-channel electroencephalogram (EEG). Bidirectional long short-term...

Space-efficient optical computing with an integrated chip diffractive neural network.

Nature communications
Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more important for realizing optical neural networks (ONNs) capable of advanced optical computing. Traditional experimental implementations need N units such as...

Deep-learning-assisted Fourier transform imaging spectroscopy for hyperspectral fluorescence imaging.

Scientific reports
Hyperspectral fluorescence imaging is widely used when multiple fluorescent probes with close emission peaks are required. In particular, Fourier transform imaging spectroscopy (FTIS) provides unrivaled spectral resolution; however, the imaging throu...

Epileptic Seizure Detection with Hybrid Time-Frequency EEG Input: A Deep Learning Approach.

Computational and mathematical methods in medicine
The precise detection of epileptic seizure helps to prevent the serious consequences of seizures. As the electroencephalogram (EEG) reflects the brain activity of patients effectively, it has been widely used in epileptic seizure detection in the pas...

Vibration-Based Loosening Detection of a Multi-Bolt Structure Using Machine Learning Algorithms.

Sensors (Basel, Switzerland)
Since artificial intelligence (AI) was introduced into engineering fields, it has made many breakthroughs. Machine learning (ML) algorithms have been very commonly used in structural health monitoring (SHM) systems in the last decade. In this study, ...

Grade classification of human glioma using a convolutional neural network based on mid-infrared spectroscopy mapping.

Journal of biophotonics
This study proposes a convolutional neural network (CNN)-based computer-aided diagnosis (CAD) system for the grade classification of human glioma by using mid-infrared (MIR) spectroscopic mappings. Through data augmentation of pixels recombination, t...

Acoustic emission corrosion feature extraction and severity prediction using hybrid wavelet packet transform and linear support vector classifier.

PloS one
Corrosion in carbon-steel pipelines leads to failure, which is a major cause of breakdown maintenance in the oil and gas industries. The acoustic emission (AE) signal is a reliable method for corrosion detection and classification in the modern Struc...

Physics-based learning with channel attention for Fourier ptychographic microscopy.

Journal of biophotonics
Fourier ptychographic microscopy (FPM) is a computational imaging technology for large field-of-view, high resolution and quantitative phase imaging. In FPM, low-resolution intensity images captured with angle-varying illumination are synthesized in ...

Deep Learning for Reconstructing Low-Quality FTIR and Raman Spectra─A Case Study in Microplastic Analyses.

Analytical chemistry
Herein we report on a deep-learning method for the removal of instrumental noise and unwanted spectral artifacts in Fourier transform infrared (FTIR) or Raman spectra, especially in automated applications in which a large number of spectra have to be...

EEG-Based Personality Prediction Using Fast Fourier Transform and DeepLSTM Model.

Computational intelligence and neuroscience
In this paper, a deep long short term memory (DeepLSTM) network to classify personality traits using the electroencephalogram (EEG) signals is implemented. For this research, the Myers-Briggs Type Indicator (MBTI) model for predicting personality is ...