ResNet-50 enhanced with ASFF improves skin lesion classification accuracy

Researchers have developed an enhanced ResNet-50 model incorporating Adaptive Spatial Feature Fusion (ASFF) to improve the accuracy of skin lesion classification. This model adaptively integrates multi-scale features, focusing on lesion-relevant regions to reduce overfitting and enhance representation. Tested on the ISIC 2020 dataset, the ASFF-based ResNet-50 achieved 93.182% accuracy, outperforming baseline models and demonstrating strong generalization on the ISIC 2019 dataset. AI

IMPACT Enhances computer-aided diagnosis systems, potentially leading to earlier and more accurate skin cancer detection.

RANK_REASON The cluster contains an academic paper detailing a new model architecture and its evaluation on benchmark datasets. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

• Adaptive Spatial Feature Fusion (ASFF)
• ISIC 2019
• ISIC 2020
• ResNet-50
• Runhao Liu

• paper
• product

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