Browsing School of Engineering by Subject "MACHINE LEARNING"
Now showing items 1-7 of 7
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Ambient Data Monitoring w/Generative Music Systems using EC & ML Techniques.
(2018)This is a position paper which describes work in progress to develop an AI/ML driven auditory ambient information system which incorporates generative music techniques and considers some of the factors involved the design ... -
Artificial Intelligence for Dynamical Systems in Wireless Communications: Modeling for the Future
(2021)Dynamical systems are no strangers in wireless communications. Our story will necessarily involve chaos, but not in the terms secure chaotic communications have introduced it: we will look for the chaos, complexity and ... -
Custom precision accelerators for energy-efficient image-to-image transformations in motion picture workflows
(SPIE, 2023)Image to Image (I2I) transformations have been an integral part of video processing workflows with applications in Image Synthesis for Virtual Productions, Segmentation, and Matting, among others. Over the years, ... -
THE DESIGN OF A SMART CITY SONIFICATION SYSTEM USING A CONCEPTUAL BLENDING AND MUSICAL FRAMEWORK, WEB AUDIO AND DEEP LEARNING TECHNIQUES
(2021)This paper describes an auditory display system for smart city data for Dublin City, Ireland. It introduces and describes the different layers of the system and outlines how they operate individually and interact with ... -
A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs
(2022)Rising connectivity in vehicles is enabling new capabilities like connected autonomous driving and advanced driver assistance systems (ADAS) for improving the safety and reliability of next-generation vehicles. This ... -
Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation
(2024)This paper proposes the use of Artificial Neural Networks (ANNs), specifically Physics-Informed Neural Networks (PINNs), for dynamic surrogate modelling of wind turbines. PINNs offer the flexibility to model complex ...