-
Notifications
You must be signed in to change notification settings - Fork 179
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Task Submission for Alzheimer’s Disease Classification Using GFNet #168
base: topic-recognition
Are you sure you want to change the base?
Task Submission for Alzheimer’s Disease Classification Using GFNet #168
Conversation
…ation set after split
<This is an initial inspection, no action is required at this point.> File Organizing: Well-organized files. Problem Solving:
Model and functions:
Code design: Good Code comment and docstring:
Difficulty: Hard. Additional Comments:
|
@wangzhaomxy Thank you for your feedback. Regarding the input channel mismatch you mentioned, I actually converted the input image to RGB in dataset.py, so I initialised the model’s input channel as 3 accordingly. |
Thanks for your feedback. |
Observational Feedback Pull Request: File Organizing: Could Better Organise but deleting unwanted Files . Commit Log: Documentation: |
Thanks for the feedback. Based on the @aniketgupta17 's feedback, I made some modification of my project. I added conclusion section into the README.md file, and re-organised the file stuctures (removed unwanted files, moved images into a folder called images). |
Marking
Marked as per the due date and changes after which aren't necessarily allowed to contribute to grade for fairness. |
Model incorrect, not GFNet therefore not hard or normal difficulty -10. Implementation does not work, module not correct -2 additionally. |
@shakes76 Thanks for your feedback. May I know what my total score of this project would be? Will it be -10+(-2)=-12 or -12 plus the score from the tutor (i.e. -12+(-10)=-22) or something else? |
Yes, it will be -22. -10 from Gayan's assessment and then -12 from my assessment given model used was neither in normal or hard difficulty. Blackboard should reflect this mark. |
Project Overview
This pull request includes a complete and demonstrable version of the GFNet algorithm for Alzheimer's disease classification task. The model uses AD and NC category images from the ADNI dataset, applying the GFNet architecture to classify these images.
Work Details
Demonstration Instructions
This pull request includes the following key files and modules:
The GFNet algorithm in this submission runs on the provided dataset and generates classification results. The inclusion of training and testing scripts allows for easy validation and replication of model results.
Validation Steps
To demonstrate the model, please follow these steps: