Rifai Chai

Senior Lecturer

Swinburne University of Technology

Australia

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About

Rifai Chai is a Senior Lecturer at Swinburne University of Technology in Australia. His research focuses on microwave imaging, biomedical signal processing, and machine learning applications in health and rehabilitation. Notable recent works include exploring innovative methods for microwave tomography and analyzing physiological signals for anxiety measurement. Dr. Chai also investigates advanced techniques for image quality evaluation and has contributed to the field of robotics with studies on exoskeletons and brain-computer interfaces.

Articles (22)

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2020

Collaborators (7)

YuKai Wang

University of Sydney

AUSTRALIA

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Jinchuan Zheng

Associate Professor

Swinburne University of Technology

AUSTRALIA

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Adrian Pranata

Senior Lecturer

RMIT University

AUSTRALIA

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Ashley R. Craig

University of Sydney

AUSTRALIA

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Ann Carrigan

Macquarie University

AUSTRALIA

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Yvonne Tran

Macquarie University

AUSTRALIA

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Hung Tan Nguyen

Emeritus Professor

University of Sydney

AUSTRALIA

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Rifai Chai

Research Interests

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About

Articles (22)

Subspace-Based Two-Step Iterative Shrinkage/Thresholding Algorithm for Microwave Tomography Breast Imaging

Non-Invasive Differential Temperature Monitoring Using Sensor Array for Microwave Hyperthermia Applications: A Subspace-Based Approach

Measuring anxiety level on phobia using electrodermal activity, electrocardiogram and respiratory signals

Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising

Deep Residual Network With Integrated StarDist Nuclei Segmentation for Papillary Thyroid Cancer Identification: A Pathologist-Inspired Approach

Can a Novel Light Weight Minimal Support Lifting Exoskeleton Modify Lifting Movement in People without Low Back Pain?

Brain-computer interface-based hand exoskeleton with bidirectional long short-term memory methods

Regression-Based Machine Learning for Predicting Lifting Movement Pattern Change in People with Low Back Pain

Hybrid Feature Extractor Using Discrete Wavelet Transform and Histogram of Oriented Gradient on Convolutional-Neural-Network-Based Palm Vein Recognition

Electric powered wheelchair control using user-independent classification methods based on surface electromyography signals

Combining Multistaged Filters and Modified Segmentation Network for Improving Lung Nodules Classification

Clustering for mitigating subject variability in driving fatigue classification using electroencephalography source-space functional connectivity features

Source-Space Brain Functional Connectivity Features in Electroencephalogram-Based Driver Fatigue Classification

Image Recovery from Synthetic Noise Artifacts in CT Scans Using Modified U-Net

Machine Learning Derived Lifting Techniques and Pain Self-Efficacy in People with Chronic Low Back Pain

Improving EEG-Based Driver Distraction Classification Using Brain Connectivity Estimators

Curvature Best Basis: A Novel Criterion to Dynamically Select a Single Best Basis as the Extracted Feature for Periocular Recognition

Optimizing CNN Hyperparameters for Blastocyst Quality Assessment in Small Datasets

Robust tracking control of a differential drive wheeled mobile robot using fast nonsingular terminal sliding mode

Edge Artificial Intelligence: Real-Time Noninvasive Technique for Vital Signs of Myocardial Infarction Recognition Using Jetson Nano

The Effect of Hypoglycemia on Spectral Moments in EEG Epochs of Different Durations in Type 1 Diabetes Patients

A Telepresence Wheelchair with 360-Degree Vision Using WebRTC

Collaborators (7)

YuKai Wang

Jinchuan Zheng

Adrian Pranata

Ashley R. Craig

Ann Carrigan

Yvonne Tran

Hung Tan Nguyen

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