Course Project

An integral part of the course is the class project (30% of the grade), which gives students a chance to apply the algorithms discussed in class to a research oriented project.

Please also keep in mind that complexity of your project topic will be taken into consideration while grading.

Deliverables

• Proposals: April 3, 2023
• Project progress reports: May 8, 2023
• Final project presentations: May 29, 2023
• Final reports: June 4, 2023
  
  

In preparing your progress and final project reports, you should use the provided LaTeX template and submit them electronically in PDF format. Late submissions will be penalized.

Collaboration Policy

Each project should be done in pairs. Of course, there may be some exceptions, depending on the enrollment. Note that students without a team will be randomly assigned to one project group.

Grading

• Proposal (2%)
• Meetings with TAs, github commits (4%)
• Progress report (6%)
• Presentation (8%)
• Final report and code (10%)

Project Proposal

Each project group should submit a half page project proposal on their specific project idea by April 3, 2023. The proposal should provide

• The research topic to be investigated,
• What data you will use,
• A list of related papers.

Meetings with TAs, and github commits

Each project group should regularly meet with the TA to discuss their progress and get feedback. Each group should maintain a GitHub repository for their project (must be viewable to the TAs and instructor). The frequency of your commits to GitHub will also be graded.

Progress Report

Due: May 8, 2023 (11:59pm)

Each project group should submit a project progress report by May 8, 2023. The report should be 4 pages and should describe the following points as clearly as possible:

• Problem to be addressed. Give a short description of the problem that you will explore. Explain why you find it interesting.
• Related work. Briefly review the major works related to your research topic.
• Methodology to be employed. Describe the method or the methods that is expected to form the basis of the project. State whether you will extend an existing method, or devise your own approach, or do a comparative study.
• Experimental evaluation. Briefly explain how you will evaluate your results. State which dataset(s) you will employ in your evaluation. Provide your preliminary results (if any).

Project Presentations

Due: May 29, 2023 (in class)

Each project group will have ~10bbm mins to present their work in class. The suggested outline for the presentations are as follows:

• High-level overview of the paper (main contributions)
• Problem statement and motivation (clear definition of the problem, why it is interesting and important)
• Key technical ideas (overview of the approach(es))
• Experimental set-up (datasets, evaluation metrics, applications)
• Strengths and weaknesses (discussion of the results obtained)

In addition to classroom presentations, each group should also prepare an engaging video presentation of their work using online tools such as PowToon, moovly or GoAnimate. The deadline is June 4, 2023.

Final Report

Due: June 4, 2023 (11:59pm)

As the last deliverable of the course project, each group is expected to submit a project report prepared using the style files provided in the course web page. The report should be 8 pages and should be structured as a research paper. It will be graded based on clarity of presentation and technical content. A typical organization of a report might follow:

• Title, Author(s).
• Abstract.
• Introduction. This section introduces the problem that you investigated by providing a general motivation and briefly discusses the approach(es) that you explored to solve this problem.
• Related Work. This section discusses relevant literature for your project topic.
• The Approach. This section gives the technical details about your project work. You should describe the representation(s) and the algorithm(s) that you employed or proposed as detailed and specific as possible.
• Experimental Results. This section presents some experiments in which you analyze the performance of the approach(es) you proposed or explored. You should provide a qualitative and/or quantitative analysis, and comment on your findings. You may also demonstrate the limitations of the approach(es).
• Conclusions. This section summarizes all your project work, focusing on the key results you obtained. You may also suggest possible directions for future work.
• References. This section gives a list of all related work you reviewed or used.