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Proposer
Christos Chrysoulas
Title
Compressing VLMs for Use on Constrained Devices
Goal
Description
Literature: sourcing and comparing model compression techniques. Implementation: use a technique from the literature to compress a pretrained VLM for use on a constrained device (e.g. Raspberry Pi). This work will be closely supervised by Tess Watt (PhD Student)
Resources
Background
Url
Difficulty Level
High
Ethical Approval
None
Number Of Students
2
Supervisor
Christos Chrysoulas
Keywords
Degrees
Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Software Engineering
Master of Science in Robotics with Industrial Application
Postgraduate Diploma in Artificial Intelligence
BSc Data Sciences
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