Dr. Azadeh Noori Hoshyar
Lecturer, Information Technology
Dr Azadeh Noori Hoshyar’s research expertise includes image processing, signal processing, machine learning and agile software development. Recently, Dr Hoshyar has focused on AI-based preventive models for structural failure. Azadeh has been involved in several projects in structural health monitoring and biomedical engineering.
Azadeh has been published widely in high-ranking peer-reviewed journals and at international conferences. She is a member of the Australian Computer Society, Institute of Electrical and Electronics Engineers, and Australian Network of Structural Health Monitoring.
In April 2020, Azadeh joined Federation University Australia as Lecturer in information technology. Prior to that, she was a postdoctoral research fellow at Bond University, and received her PhD from Western Sydney University in 2019. She has a master’s in engineering from the University of Technology, Sydney and a master’s in information technology (computer science) from the National University of Malaysia. Azadeh has worked in the software industry for about four years.
Intelligent Feature Selection Algorithm Using SA-SVM Classification for Skin Cancer Diagnosis
An Optimal Scheduling Method in IoT-Fog-Cloud Network Using Combination of Aquila Optimizer and African Vultures Optimization
Corrosion and coating defect assessment of coal handling and preparation plants (CHPP) using an ensemble of deep convolutional neural networks and decision-level data fusion
Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges
Multi-Dataset Hyper-CNN for Hyperspectral Image Segmentation of Remote Sensing Images
Multiheaded deep learning chatbot for increasing production and marketing
Proposed Machine Learning Techniques for Bridge Structural Health Monitoring: A Laboratory Study
A comprehensive taxonomy for structure and material deficiencies, preventions and remedies of timber bridges
As timber bridges have become archaic, they are no longer able to effectively service their...
KIDNet: A Knowledge-Aware Neural Network Model for Academic Performance Prediction
Machine Learning Based Biosignals Mental Stress Detection
Nonlinear characterization of magnetorheological elastomer-based smart device for structural seismic mitigation
Magnetorheological elastomer (MRE) has been demonstrated to be effective in structural vibration...
Using vector agents to implement an unsupervised image classification algorithm
Analysis of failure in concrete and reinforced-concrete beams for the smart aggregate–based monitoring system
Monitoring of structures and defining the severity of damages that occur under loading are...
Automated health condition diagnosis of in situ wood utility poles using an intelligent non-destructive evaluation (NDE) framework
Wood utility poles are widely applied in power transmission and telecommunication systems in...
Structural damage detection and localization using a hybrid method and artificial intelligence techniques
In this article, an intelligent scheme for structural damage detection and localization is...
Algorithm development for the non-destructive testing of structural damage
Monitoring of structures to identify types of damages that occur under loading is essential in...
Statistical Features and Traditional SA-SVM Classification Algorithm for Crack Detection
In recent years, the interest in damage identification of structural components through...
Millimeter Wave Imaging of Notches in Metal Specimens under Dielectric Coating Using Image Processing
Structural health monitoring is one of the main concerns in infrastructure engineering since it...
Structural damage detection of a concrete based on the autoregressive all-pole model parameters and artificial intelligence techniques
Over the past few decades, damage identification in structural components has been the crucial...
Structural damage identification using millimeter wave imaging and image processing
In the past decades, structural health monitoring (SHM) has received wide attention in preventing...
Microwave imaging of composite materials using image processing
This paper presents the results of application of a relatively simple microwave continuous wave...
A binary level set method based on k-Means for contour tracking on skin cancer images
A great challenge of research and development activities have recently highlighted in segmenting...
Comparing the performance of various filters on skin cancer images
Noise removing from an image is an important task in different applications such as medical which...
The beneficial techniques in preprocessing step of skin cancer detection system comparing
Automatic diagnostics of skin cancer is one of the most challenging problems in medical image...
Automated segmentation of skin lesions: Modified Fuzzy C mean thresholding based level set method
Accurate segmentation of skin lesion can play a vital role in early detection of skin cancer....
Review on automatic early skin cancer detection
Skin cancer is increasing in different countries especially in Australia. Early detection of skin...
Vein matching using artificial neural network in vein authentication systems
Personal identification technology as security systems is developing rapidly. Traditional...
Review on finger vein authentication system by applying Neural Network
Biometric technologies are automated methods for recognizing individuals based on biological and...