Now showing items 1-7 of 7
Detection of Double and Triple Compression in Videos for Digital Forensics Using Machine Learning
Digital video forensics is the process of analysing, examining and comparing a video for use in legal matters and court cases. In digital video forensics, the main aim is to detect and identify video forgery and manipulation ...
Data Embedding and Extraction in Scrambled Video using Machine Learning
Data embedding in videos and images has various important applications such as digital rights management (DRM), content authentication, copyright protection, error resiliency and concealment as well as law enforcement. ...
EEG-Based Semantic Vigilance Level Classification Using Directed Connectivity Patterns and Graph Theory Analysis
This paper proposes two novel methods to classify semantic vigilance levels by utilizing EEG directed connectivity patterns with their corresponding graphical network measures. We estimate the directed connectivity using ...
Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
Many Internet of Things (IoT) applications deploy identical end devices like sensor nodes or surveillance cameras in an organization. The purpose of this thesis was to determine if a malicious physical substitution of one ...
Improvement of Dialysis Dosing Using Big Data Analytics
Data is transforming the healthcare sector and making it more dependent on data science. Data science is becoming a critical tool that allows looking at the data generated from various sources, such as patient health ...
Machine Learning-Based Approach for EV Charging Behavior
As smart city applications are moving from conceptual models to the development phase, smart transportation, of smart cities’ applications, is gaining ground nowadays. Electric vehicles (EVs) are considered to be one of ...