本项目采用了U2Net、ConvNext、Swin Transformer等多种深度学习模型，用于医学图像的分割与诊断。该平台利用MobileViT等轻量级模型，实现了在边缘设备上的实时病变分析，并通过Jetson Nano的GPU加速功能大幅提升了诊断效率。平台具备用户友好的界面，支持多种操作系统与硬件架构，并通过不断的数据积累和机器学习，提升诊断算法的准确性。此外，平台提供了皮肤病健康医典模块，方便用户查询相关医学信息，并具备较高的扩展性与合作推广潜力。
☆14Aug 15, 2024Updated 2 years ago
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