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Brain Tumor Classification Using Swin Transformer
该模型是基于Swin Transformer架构的脑肿瘤图像分类模型，在图像分类任务上表现出色，准确率达到99.49%。
Downloads 103
Release Time : 1/25/2023
Model Overview
这是一个微调后的Swin Transformer模型，专门用于脑肿瘤图像的分类任务。模型在评估集上表现出接近完美的分类性能。
Model Features
高精度分类
在脑肿瘤分类任务上达到99.49%的准确率、F1分数、召回率和精确率
基于Swin Transformer
采用先进的Swin Transformer架构，适合处理视觉任务
高效微调
在预训练模型基础上仅需少量训练即可获得优异性能
Model Capabilities
医学图像分类
脑肿瘤识别
图像特征提取
Use Cases
医疗诊断
脑肿瘤筛查
用于辅助医生识别脑肿瘤类型
分类准确率99.49%
医学影像分析
自动分析MRI等医学影像中的异常情况
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