Question9: A classifier which classifies if a scan classifies as normal or Melonoma

[jass420]

This classifier classifies if a scan classifies as normal or Melonoma with an accuracy of 80% and uses Siamese network architecture.

[hanemma7moud]

This is an initial inspection, no action is required at this point

Recognition Problem : total : 18
Well Done !

1. Solves problem: The solution is appropriate for the problem (3)
   Correct use of a Siamese Network + contrastive loss for melanoma vs benign and the final model achieves the target performance (~80% test accuracy).
   However:

• No embedding visualisation (t-SNE or UMAP)
• other plots to evaluate the performance (loss, accuracy, ...etc)

2. Implementation functions : The code appears to be functional (3)

Good design: design is fairly strong(1)
Commenting: good(1)
Difficulty: Hard (10)

Overall good work, thanks

[wangzhaomxy]

47490165

[gayanku]

Marking

Good/OK/Fair Practice (Design/Commenting, TF/Torch Usage)
	Adequate design and implementation.	-1
	Spacing and comments.
	Header blocks.
Recognition Problem
	OK solution to problem.	-1
	Driver Script present.
	File structure present.
	Good Usage & Demo & Visualisation & Data usage.
	Module present.
	Commenting present.
	No Data leakage found.
	Difficulty : Hard. Hard Difficulty : Siamese
Commit Log
	Good Meaningful commit messages.
	Good Progressive commits.
Documentation
	Readme :Acceptable.	-2
	Model/technical explanation :Good.
	Description and Comments :Good.
	Markdown used and PDF submitted.
Pull Request
	Successful Pull Request (Working Algorithm Delivered on Time in Correct Branch).
	No Feedback required.
	Request Description is good.
TOTAL		-4

Marked as per the due date and changes after which aren't necessarily allowed to contribute to grade for fairness.
Subject to approval from Shakes