We introduce the Feature Feedback-Based Pseudo-Label Learning (FF-PLL) framework,

which enhances acne grading accuracy through innovative techniques like iterative pseudo-label refinement and all-facial skin segmentation.

Our experiments show promising results, achieving high accuracy and sensitivity,

making FF-PLL a viable solution for standardized acne assessment in clinical settings.

We invite you to read our paper and share your thoughts!​

 

Feature Feedback-Based Pseudo-Label Learning for Multi-Standards in Clinical Acne Grading

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