我的数据格式如下。
im1类
im2类
img3 class4
一个人能够提出最佳模型来记录这一数据。
我认为,我们可以通过在最后一层使用草原而不是软顶来进行多级的多标签分类。
For example last layer will have 1 nodes for each class giving the probability of that class.
Assume 5级加Dense(5, 启动=“sigmoid”)是最后一个。 第一个图像“img1”的地面真相为[1,1,1,00],“img3”为[0,0,1,01]。
你们需要使问题具体化。
如果你想要将Ig1分类为1、2和3类,那么你可以重新界定包括3类的标签。
例如,<代码>类别A包括第1、2和3类。
<代码>B包括第1类和第2类。
此外,还有4个班级。
[第1类,第2类,第3类,第4类]
现在,你的数据集由6个班组成。
[第1类,第2类,第3类,第4类,A类,B类
作为6个类别,你可以解决这个问题。
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