数据融合matlab代码-KFNN-Master:基于卡尔曼滤波的多神经网络融合代码
数据融合matlab代码KFNN大师
基于卡尔曼滤波的多神经网络融合代码
整个系统由两部分组成：神经网络的噪声估计和基于kfnn的多神经网络的融合。
数据集
神经网络的噪声估计和融合性能评价。
应用./ImageNet/val.py处理ImageNet并将数据组织为以下结构。
/ImageNet
/val
/n01440764
images
/n01443537
images
/train
/test
ImagNet中的预训练模型
借助中提供的开放式预训练模型，我们使用了16种经典的预训练模型作为基准，包括NASNetlarge，AlexNet，DenseNet121，ResNet18，ResNet34，ResNet50，ResNet101，ResNet152，VGG11，VGG11_bn，VGG13，VGG13_bn，VGG16，VGG16_bn，VGG19，
VGG19_bn
。
我们分别评估了它们在ImageNet上的性能。
我们按照，完成了预训练模型的下载和应用。
验证集的准确性（单个模型）
在我们的机器上，下表显示了预训练模型的验证准确性。
预训练模型
帐户@
1
NASNe
文件下载
资源详情
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