Difference between revisions of "Projects:2020s2-7233 Image Denoising with Dictionaries"
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== Abstract == | == Abstract == | ||
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== Introduction == | == Introduction == | ||
| − | + | Dictionary learning is a topical area of signal processing research. It shares similarities but also crucial differences from other machine learning ideas such as deep learning neural networks. It rests on the idea of sparse representations using a well-designed dictionary that can lead to high performance in a wide range of signal processing applications. Image denoising is one of many signal processing applications. The idea developed here can easily be transferred to other application area. | |
== Project Team == | == Project Team == | ||
=== Project Students === | === Project Students === | ||
Revision as of 22:25, 14 September 2020
Contents
Abstract
Introduction
Dictionary learning is a topical area of signal processing research. It shares similarities but also crucial differences from other machine learning ideas such as deep learning neural networks. It rests on the idea of sparse representations using a well-designed dictionary that can lead to high performance in a wide range of signal processing applications. Image denoising is one of many signal processing applications. The idea developed here can easily be transferred to other application area.
Project Team
Project Students
- Muhammad Haziq Saharuddin
- Muhammad Faizal Azhar
- Chen Chen
Project Supervisor
- Associate Professor Brian Ng
