Thesis Topic Details

Topic ID:
609
Title:
Semantic-Sensitive Image Classification
Supervisor:
Jian Zhang
Research Area:
Artificial Intelligence
Associated Staff
Assessor:
Wei Wang
Topic Details
Status:
Active
Type:
R & D
Programs:
CS CE BIOM BINF SE
Group Suitable:
No
Industrial:
Pre-requisites:
C/C++, Advanced Math
Description:
Due to the rapidly growing amount of digital image data on the Internet and in digital libraries, there is a great need for large image database management and effective image classification tools. Image classification algorithms typically attempt to label an image as either true or false based on the presence or absence of some target concept with semantic meaning, or assign an image into one of several semantic categories. Potential applications of image classification range from organizing a personal photo collection to detecting specific objects within a surveillance system. This project is focused on improving and enhancing the image classification system developed by Multimedia and Video Communication Group at NICTA. The main tasks involved in this project are: (1) implementing an image segmentation technique and integrating it into the image classification system; (2) modifying some implementations and improving the efficiency of the system. You will have an opportunity to learn how to use image processing, image retrieval, and machine learning techniques to solve several critical problems.
Comments:
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