Automated tools are crucial for efficient acne severity assessment due to variability in manual grading. The proposed method combines label smoothing with label distribution learning to enhance acne diagnostics by managing label uncertainty effectively. By incorporating severity scale information into lesion counting and simplifying severity class definitions, the model demonstrates improved performance on the ACNE04 dataset.
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by Kirill Prokh... at arxiv.org 03-04-2024
https://arxiv.org/pdf/2403.00268.pdfDeeper Inquiries