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Skin Cancer Image Classification
基於視覺變換器(ViT)的皮膚癌圖像分類模型，可識別7種皮膚病變類型
Downloads 3,309
Release Time : 3/8/2024
Model Overview
該模型採用ViT架構，專為皮膚癌圖像分類設計，能夠將皮膚病變圖像分類為7種不同類型，包括良性角化病樣病變、基底細胞癌等。
Model Features
高性能ViT架構
採用在ImageNet21k上預訓練的視覺變換器模型，具有強大的圖像特徵提取能力
專業醫療分類
針對7種皮膚癌相關病變類型優化，分類準確率高
快速收斂
僅需5輪訓練即可達到96.95%的驗證準確率
Model Capabilities
皮膚病變圖像分類
醫療圖像分析
皮膚病輔助診斷
Use Cases
醫療輔助診斷
皮膚癌篩查
用於輔助醫生進行皮膚癌早期篩查
驗證準確率達96.95%
皮膚病分類
自動分類7種常見皮膚病變類型
訓練準確率達96.14%
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