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Proposer
Radu-Casian Mihailescu
Title
Explainable AI for Deep Learning Models: Better understanding of their decision-making processes
Goal
Description
Deep neural networks are very complex, and their decisions can be hard to interpret. In this project we want to use Explainable AI (XAI) to understand why a deep neural network makes a classification decision or prediction. XAI can be used to determine the importance of features of the input data, as a proxy for the importance of the features to the deep neural network. It has a wide range of applications across various domains where the transparency, interpretability, and accountability of AI systems are essential such as health, finance, or autonomous systems.
Resources
Background
Url
Difficulty Level
Moderate
Ethical Approval
None
Number Of Students
1
Supervisor
Radu-Casian Mihailescu
Keywords
Degrees
Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Bachelor of Science in Information Systems
Bachelor of Science in Software Development for Business (GA)
Master of Engineering in Software Engineering
Master of Design in Games Design and Development
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Business Information Management
Master of Science in Computer Science for Cyber Security
Master of Science in Computer Systems Management
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Human Robot Interaction
Master of Science in Information Technology (Business)
Master of Science in Information Technology (Software Systems)
Master of Science in Network Security
Master of Science in Robotics
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Bachelor of Engineering in Robotics
Bachelor of Science in Computer Science (Cyber Security)
Master of Science in Robotics with Industrial Application
Postgraduate Diploma in Artificial Intelligence
Bachelor of Science in Statistical Data Science