Reference no: EM13374926
Introduction
Research and discover more in-depth knowledge about topics in Pattern Recognition.
You need first to choose a topic. The best topic will be the one you are most interested in or a topic from your research project you are working on.
You could also choose your topic from the following list.
1. Face recognition: a comparison of eigen-analysis and frequency based techniques.
2. Data clustering: a comparison of k-Means and Mean shift techniques.
3. A short review of Boosting.
4. Density estimation: an exploration of kernel methods.
5. Web page classification.
You are allowed to work alone or in groups of no more than two (2) students. Marks are awarded to students based on their individual contributions. If you work in a group, a signed statement of individual contributions must be included otherwise marks will not be awarded. Each student in a group must contribute to all aspects of the assignment including programming, experimenting and paper writing. The statement must include specifics of individual contributions, not only a percentage. The statement should be scanned and included in your submission. One submission is required for each group.
Consider the following to give you an idea of what is expected.
• Go to the library and search the databases for papers or books on the topic you have chosen.
• A review paper or a book is good starting point.
• Quickly read about the topic to give you an idea of what it is about.
• Think about the data set that you will need to perform experiments. This will allow you to write a good term paper. It is also possible that you generate synthetic data.
• You need to implement something to demonstrate that you know what you are talking about. You may use any programming language but Matlab is strongly recommended. You can write the codes yourself or use any code that is available in the public domain.
In case you use code from public domain, you are required to properly cite its source and describe the details of the algorithms that the code implements, and include the code in your submission.
Use the following headings in your paper:
1. Introduction -
You should describe the topic and the kind of problem that can be solved using the techniques you have chosen. You should also write about the possible application areas.
2. Background theory and related work
You are supposed to write about the theoretical foundation of the topic and related work from literature. Aim to provide some theoretical and latest developments and how these fit with the solution or experiments that you will be conducting.
3. Experimental setup and description of data set
In this section you are to write about the design of your experiments and the preparation of your data set.
4. Results
In this section you are supposed to present the results you obtained. This is where you present the graphs and any other techniques of showing your results with discussions on how the results related to your solutions.
Information from academic resources used in your reports should be properly cited with references. All submissions should include computer code that produced your results with a README.txt file that describes how to compile and run your code to reproduce the results.
Download:- CPS.zip