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COMP9444 Project Summary


I. Introduction

<Write introduction of the project here. You should describe the aim of the paper, the importance of the problem addressed, its applications, and your contribution towards improving current practice using the proposed solution.>

II. Related Work

<Provide a summary of some related work. Highlight salient findings from these papers and clearly provide limitations of existing work and what could be done to improve it. This will lay the foundation of your own work.>

III. Methods

<Describe briefly about the method(s) used in the project. Also, provide your rationale for the choice out of alternative methods. You should also provide details whether pre-trained models have been taken, and/or fine-tuning has been done. Also, provide details which you think are worth mentioning which can provide more context to your project evaluator(s). >

IV. Experimental Setup

< Describe briefly about the dataset and its key features (e.g., number of samples, number of classes, etc.). You should clearly highlight source of the dataset (preferably URL) so that evaluator(s) can have to look at the dataset used. Describe any key findings based on the data exploration. Describe the evaluation strategy used and key model hyperparameters used.>

V. Results

<Provide key experimental results from your experiment(s). Describe the main findings from the evaluation. Provide analysis whether the findings are good enough to be deployed in real-world application(s). Describe how the proposed solution is different from other proposed solution(s) based on the literature. Where your proposed solution stands in terms of standard evaluation compared to existing state-of-the-art.>

VI. Conclusions

<Describe contribution(s) in the project. What are the key strength(s) of the proposed solution? Describe any limitation(s) of your current study and how it can be improved given more time for the project.>

Note: Your project summary should be in at most 4 pages (excluding references). There is no limit on the number of references. Any main text beyond the 4-page limit will be ignored by the evaluator(s). 




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