Task $1$:

a real$-$world binary image classification problem of your interest

$1-$

Apply deep learning model to solve this problem "COVIDx CXR$-4$

Chest x$-$ray images for the detection of COVID$-19"$ using Python programming language. Provide the screenshot of the code along with respective output

$2-$

Write a report that discusses the problem$-$solving process that must include the following.

$3-$

Abstract: Briefly describe your problem, approach, and key results

$4-$

Introduction: Provide a general introduction to deep learning and its applications in solving real$-$world problems.

$5-$

Literature review: Discuss published works $($minimum $2)$ that relate to your project. How is your approach similar or different from others?

$6-$

Problem statement: Describe the problem you are working on$,$ why is it important?

$7-$

Data: Description of the dataset which includes a description of the data you are working with for your case study. What type of data is it$?$ What is the source of data? How much data are you working with? Did you have to do any preprocessing to use this data in your project?

$8-$

Methods: Discuss your approach for solving the problems that you set up in task "Problem statement" which includes the description of the proposed convolutional neural network model and the pre$-$trained model used. You should demonstrate that you have applied ideas and skills built up during the semester to tackle your problem of choice.

$9-$

Result Evaluation: The following need to be considered:

a$.$ Impact of overfitting$/$underfitting and respective solution $($at least one solution$)$

b$.$ Include the performance evaluation of your method and compare it with the pre$-$trained model based on at least $2$ classification evaluation metrics. Show the comparison in the form of a table.

$10-$

Conclusion: Summarize your key results $-$ what have you learned? Suggest ideas for future extensions or new applications of your ideas.