Author:Michael Lornwood

Publications
Integrating Mathematical Models for Enhanced Object Detection: a Hybrid Deep Learning Approach Mo Zhang, Kon Yang, Mo Chang and Michael Lornwood EasyChair Preprint 15596
Deep Learning-Driven Real-Time Anomaly Detection in SDNs: a Performance Comparison Hoo Wang, Che Leo, John Davis, Sarah Smith, Daniel Taylor and Michael Lornwood EasyChair Preprint 15583
A Machine Learning-Driven Approach to XML-Based IP Network Configuration Optimization Hoo Wang, Che Leo, John Davis, Sarah Smith, Daniel Taylor and Michael Lornwood EasyChair Preprint 15560
Advancing Machine Learning: Comparative Analysis of Techniques Alex Wang, Maria Kin, Piter Wen, Rusel Deniz, Li Wei and Michael Lornwood EasyChair Preprint 15546
A Novel Algorithmic Approach for Privacy-Preserving Data Synthesis via Randomized Mixing Michael Lornwood, Li Wei and Emily Wilson EasyChair Preprint 15513
Mathematics-Driven Enhancements in Object Detection: a Hybrid Deep Learning Framework Michael Lornwood EasyChair Preprint 15504

Keyphrases

adaptive systems, AI-driven Framework, Algorithms³, analysis, anomaly detection, CNN², Configuration Management, Convolutional Neural Networks (CNN), data privacy, dataset synthesis, deep learning³, differential privacy, machine learning³, model, Network Security, Privacy-Preserving Algorithms, Randomized Mixing, Reinforcement Learning, Software Defined Networking (SDN), ViT².