Faisal Saeed

Senior Lecturer

Birmingham City University

United Kingdom

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Faisal Saeed is a Senior Lecturer at Birmingham City University in the United Kingdom. His research areas include deep learning applications in healthcare and disease detection, intelligent resource management in agriculture, and malicious content detection in social media. He has contributed to various recent articles focusing on topics such as Alzheimer's disease detection, skin disease diagnosis across diverse skin tones, and enhancing intrusion detection systems. His work emphasizes the integration of machine learning methods for practical and sustainable solutions in various domains.

Faisal Saeed

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Articles (26)

Early detection of Alzheimer's disease using deep learning methods

IoT-UAV-Enabled Intelligent Resource Management in Low-Carbon Smart Agriculture Using Federated Reinforcement Learning

Early Detection of Skin Diseases Across Diverse Skin Tones Using Hybrid Machine Learning and Deep Learning Models

Topic-aware neural attention network for malicious social media spam detection

Knowledge Distillation for Lightweight and Explainable Intrusion Detection in Resource-Constrained Consumer Devices

Sustainable Environmental Monitoring: Multistage Fusion Algorithm for Remotely Sensed Underwater Super-Resolution Image Enhancement and Classification

Enhancing Intrusion Detection Systems Using a Deep Learning and Data Augmentation Approach

SMS Scam Detection Application Based on Optical Character Recognition for Image Data Using Unsupervised and Deep Semi-Supervised Learning

Determinants of Intention to Use Simulation-Based Learning in Computers and Networking Courses: An ISM and MICMAC Analysis

Multi-Modal Features Representation-Based Convolutional Neural Network Model for Malicious Website Detection

An Ensemble Machine Learning and Data Mining Approach to Enhance Stroke Prediction

Machine Learning-Based Predictive Models for Detection of Cardiovascular Diseases

AI-Based Wireless Sensor IoT Networks for Energy-Efficient Consumer Electronics Using Stochastic Optimization

Addressing Behavioral Drift in Ransomware Early Detection Through Weighted Generative Adversarial Networks

IoT-Driven Visual Surveillance: Temporal Masking for Adaptive Motion Compensation in Imaging Technology

Parkinson’s Disease Detection Using Filter Feature Selection and a Genetic Algorithm with Ensemble Learning

Empowering Precision Medicine: Unlocking Revolutionary Insights through Blockchain-Enabled Federated Learning and Electronic Medical Records

Securing Secrets in Cyber-Physical Systems: A Cutting-Edge Privacy Approach with Consortium Blockchain

Motion Capture Technologies for Ergonomics: A Systematic Literature Review

DenseNet-201 and Xception Pre-Trained Deep Learning Models for Fruit Recognition

Dimension Reduction and Classifier-Based Feature Selection for Oversampled Gene Expression Data and Cancer Classification

An Adaptive Early Stopping Technique for DenseNet169-Based Knee Osteoarthritis Detection Model

Hybrid Filter and Genetic Algorithm-Based Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data

An Intelligent Early Flood Forecasting and Prediction Leveraging Machine and Deep Learning Algorithms with Advanced Alert System

A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

Application of Machine Learning to Predict COVID-19 Spread via an Optimized BPSO Model

Collaborators (10)

Sultan Noman Qasem

Fuad Abdulgaleel Abdoh Ghaleb

Mohammad Iranmanesh

Tawfik Al-Hadhrami

Waheb A. Jabbar

AbdulRahman Alsewari

Jordan Allison

Abdulwahab Almazroi

Ibukun Omotayo Muyide

Faisal S. Alsubaei

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