AIMC Topic: Fourier Analysis

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Recurrent neural networks for time domain modelling of FTIR spectra: application to brain tumour detection.

The Analyst
Attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy alongside machine learning (ML) techniques is an emerging approach for the early detection of brain cancer in clinical practice. A crucial step in the acquisition of an...

Phonocardiogram transfer learning-based CatBoost model for diastolic dysfunction identification using multiple domain-specific deep feature fusion.

Computers in biology and medicine
Left ventricular diastolic dyfunction detection is particularly important in cardiac function screening. This paper proposed a phonocardiogram (PCG) transfer learning-based CatBoost model to detect diastolic dysfunction noninvasively. The Short-Time ...

Classification Approach for Attention Assessment via Singular Spectrum Analysis Based on Single-Channel Electroencephalograms.

Sensors (Basel, Switzerland)
Attention refers to the human psychological ability to focus on doing an activity. The attention assessment plays an important role in diagnosing attention deficit hyperactivity disorder (ADHD). In this paper, the attention assessment is performed vi...

Exploration of Effective Time-Velocity Distribution for Doppler-Radar-Based Personal Gait Identification Using Deep Learning.

Sensors (Basel, Switzerland)
Personal identification based on radar gait measurement is an important application of biometric technology because it enables remote and continuous identification of people, irrespective of the lighting conditions and subjects' outfits. This study e...

Empirical Mode Decomposition-Based Feature Extraction for Environmental Sound Classification.

Sensors (Basel, Switzerland)
In environment sound classification, log Mel band energies (MBEs) are considered as the most successful and commonly used features for classification. The underlying algorithm, fast Fourier transform (FFT), is valid under certain restrictions. In thi...

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...

Predicting the Likelihood of Colorectal Cancer with Artificial Intelligence Tools Using Fourier Transform Infrared Signals Obtained from Tumor Samples.

Applied spectroscopy
The early and accurate detection of colorectal cancer (CRC) significantly affects its prognosis and clinical management. However, current standard diagnostic procedures for CRC often lack sensitivity and specificity since most rely on visual examinat...

Bearing Fault Diagnosis Using Lightweight and Robust One-Dimensional Convolution Neural Network in the Frequency Domain.

Sensors (Basel, Switzerland)
The massive environmental noise interference and insufficient effective sample degradation data of the intelligent fault diagnosis performance methods pose an extremely concerning issue. Realising the challenge of developing a facile and straightforw...

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...

Road Surface Anomaly Assessment Using Low-Cost Accelerometers: A Machine Learning Approach.

Sensors (Basel, Switzerland)
Roads are a strategic asset of a country and are of great importance for the movement of passengers and goods. Increasing traffic volume and load, together with the aging of roads, creates various types of anomalies on the road surface. This work pro...