AMAD ZAFAR

Research Professor

Sejong University

South Korea

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About

Amad Zafar is a Research Professor at Sejong University, South Korea. His research areas include artificial intelligence applications in medical imaging, specifically in the diagnosis of Alzheimer's disease and skin lesions, as well as optimization techniques in control systems and scheduling problems. He has recently published articles focusing on deep learning frameworks for health diagnostics and innovative techniques for parameter estimation and feature selection.

Articles (15)

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

Collaborators (7)

Jong Hyuk Byun

Pusan National University

SOUTH KOREA

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kwangsu kim

Assistant professor

Pusan National University

SOUTH KOREA

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Muhammad Umair Ali

Sejong University

SOUTH KOREA

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Muhammad Raheel Bhutta

SOUTH KOREA

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M A Parvez Mahmud

University of Sydney

AUSTRALIA

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Waqas Ahmed

Aalborg University

DENMARK

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Kamran Ali Khan Niazi

Aarhus University

DENMARK

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AMAD ZAFAR

Research Interests

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Articles (15)

Novel Robust Estimation-Based Control of One-Sided Lipschitz Nonlinear Systems Subject to Output and Input Delays

Artificial Neural Network-Based Data-Driven Parameter Estimation Approach: Applications in PMDC Motors

MRI-Driven Alzheimer’s Disease Diagnosis Using Deep Network Fusion and Optimal Selection of Feature

Enhancing Oral Squamous Cell Carcinoma Detection Using Histopathological Images: A Deep Feature Fusion and Improved Haris Hawks Optimization-Based Framework

An Isolated CNN Architecture for Classification of Finger-Tapping Tasks Using Initial Dip Images: A Functional Near-Infrared Spectroscopy Study

BU-DLNet: Breast Ultrasonography-Based Cancer Detection Using Deep-Learning Network Selection and Feature Optimization

OptEF-BCI: An Optimization-Based Hybrid EEG and fNIRS–Brain Computer Interface

Hybridization of Particle Swarm Optimization with Variable Neighborhood Search and Simulated Annealing for Improved Handling of the Permutation Flow-Shop Scheduling Problem

Metaheuristic Optimization-Based Feature Selection for Imagery and Arithmetic Tasks: An fNIRS Study

WBM-DLNets: Wrapper-Based Metaheuristic Deep Learning Networks Feature Optimization for Enhancing Brain Tumor Detection

A Comparison and Introduction of Novel Solar Panel’s Fault Diagnosis Technique Using Deep-Features Shallow-Classifier through Infrared Thermography

Enhancing Skin Lesion Detection: A Multistage Multiclass Convolutional Neural Network-Based Framework

A Robust Computer-Aided Automated Brain Tumor Diagnosis Approach Using PSO-ReliefF Optimized Gaussian and Non-Linear Feature Space

Reduce-Order Modeling and Higher Order Numerical Solutions for Unsteady Flow and Heat Transfer in Boundary Layer with Internal Heating

A State-Observer-Based Protection Scheme for AC Microgrids with Recurrent Neural Network Assistance

Collaborators (7)

Jong Hyuk Byun

kwangsu kim

Muhammad Umair Ali

Muhammad Raheel Bhutta

M A Parvez Mahmud

Waqas Ahmed

Kamran Ali Khan Niazi

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