A5006071214- Network Security and Intrusion Detection
- Cardiac Imaging and Diagnostics
- Anomaly Detection Techniques and Applications
- Advanced X-ray and CT Imaging
- Radiomics and Machine Learning in Medical Imaging
- Internet Traffic Analysis and Secure E-voting
- Anatomy and Medical Technology
- Radiation Dose and Imaging
- Cardiomyopathy and Myosin Studies
- Cardiac, Anesthesia and Surgical Outcomes
- Shoulder Injury and Treatment
- Retinal Imaging and Analysis
- Privacy-Preserving Technologies in Data
- Surgical Simulation and Training
- Advanced Malware Detection Techniques
- Medical Image Segmentation Techniques
- Medical Imaging Techniques and Applications
- Cardiovascular Disease and Adiposity
Glasgow Caledonian University
2023
Ospedale Versilia
2021-2022
Piaggio (Italy)
2010
The number of Internet Things (IoT) devices has increased considerably in the past few years, which resulted an exponential growth cyber attacks on IoT infrastructure. As a consequence, prompt detection environments through use Intrusion Detection Systems (IDS) become essential. This article proposes novel approach to intrusion based stacking ensemble deep learning (DL) models. is named Deep Integrated Stacking for (DIS-IoT) and it combines four different DL models into fully connected...
The number of Internet Things (IoT) devices has increased considerably in the past few years, resulting a large growth cyber attacks on IoT infrastructure. As part defense depth approach to cybersecurity, intrusion detection systems (IDSs) have acquired key role attempting detect malicious activities efficiently. Most modern approaches IDS are based machine learning (ML) techniques. majority these centralized, which implies sharing data from source central server for classification. This...
Abstract Radiomics is emerging as a promising and useful tool in cardiac magnetic resonance (CMR) imaging applications. Accordingly, the purpose of this study was to investigate, for first time, effect image resampling/discretization filtering on radiomic features estimation from quantitative CMR T1 T2 mapping. Specifically, maps 26 patients with hypertrophic cardiomyopathy (HCM) were used estimate 98 7 different resampling voxel sizes (at fixed bin width), 9 widths size), spatial filters...
The number of Internet Things (IoT) devices has increased considerably in the past few years, which resulted an exponential growth cyber attacks on IoT infrastructure. As a consequence, prompt detection environments through use Intrusion Detection Systems (IDS) become essential. This article proposes novel approach to intrusion based stacking ensemble deep learning (DL) models. is named Deep Integrated Stacking for (DIS-IoT) and it combines four different DL models into fully connected...
Abstract Radiomics is emerging as a promising and useful tool in cardiac magnetic resonance (CMR) imaging applications. Accordingly, the purpose of this study was to investigate, for first time, effect image preprocessing filtering on radiomic features estimation from quantitative CMR T1 T2 mapping. Specifically, maps 26 patients with hypertrophic cardiomyopathy (HCM) were used estimate 98 7 different resampling voxel sizes (at fixed bin width), 9 widths size), spatial filters size/bin...