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Fourier Analysis

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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 ...

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...

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, ...

Deep neural architectures for dialect classification with single frequency filtering and zero-time windowing feature representations.

The Journal of the Acoustical Society of America
The goal of this study is to investigate advanced signal processing approaches [single frequency filtering (SFF) and zero-time windowing (ZTW)] with modern deep neural networks (DNNs) [convolution neural networks (CNNs), temporal convolution neural n...

Frontal lobe real-time EEG analysis using machine learning techniques for mental stress detection.

Journal of integrative neuroscience
Stress has become a dangerous health problem in our life, especially in student education journey. Accordingly, previous methods have been conducted to detect mental stress based on biological and biochemical effects. Moreover, hormones, physiologica...

Gravitational Wave-Signal Recognition Model Based on Fourier Transform and Convolutional Neural Network.

Computational intelligence and neuroscience
The recent detection of gravitational waves is a remarkable milestone in the history of astrophysics. With the further development of gravitational wave detection technology, traditional filter-matching methods no longer meet the needs of signal reco...

Online Education Classroom Intelligent Management System Based on Tensor CS Reconstruction Model.

Computational intelligence and neuroscience
To study a high-efficiency online classroom intelligent management system, this article builds an artificial intelligence classroom management system based on the tensor CS reconstruction model. Moreover, this study uses the cosine function to repres...

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...

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...