featureinputlayer and convolution1dlayer

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san su
san su el 20 de Mzo. de 2022
Comentada: yanqi liu el 22 de Mzo. de 2022
featureinputlayer matches fullyconnectedlayer but not matches convolution1dlayer

Respuestas (1)

yanqi liu
yanqi liu el 21 de Mzo. de 2022
layers = [
featureInputLayer(100,'Name','input')
fullyConnectedLayer(5, 'Name','fc')
softmaxLayer('Name','sm')
classificationLayer('Name','classification')]
layers =
4×1 Layer array with layers: 1 'input' Feature Input 100 features 2 'fc' Fully Connected 5 fully connected layer 3 'sm' Softmax softmax 4 'classification' Classification Output crossentropyex
layers2 = [
featureInputLayer(100,'Name','input')
convolution1dLayer(50, 3,'Stride',1, 'Name','cnn1d')
fullyConnectedLayer(5, 'Name','fc')
softmaxLayer('Name','sm')
classificationLayer('Name','classification')]
layers2 =
5×1 Layer array with layers: 1 'input' Feature Input 100 features 2 'cnn1d' Convolution 3 50 convolutions with stride 1 and padding [0 0] 3 'fc' Fully Connected 5 fully connected layer 4 'sm' Softmax softmax 5 'classification' Classification Output crossentropyex
  4 comentarios
san su
san su el 22 de Mzo. de 2022
Editada: san su el 22 de Mzo. de 2022
您好!matlab这个数据要通过arrayDatastore和combine处理下才能训练,也不太好发数据。后来用imageinputlayer代替了featureinputlayer就解决了,不过想要在fullyconnectedlayer后面接convolution1dlayer是不行的。和上面图中的报错一样,程序根本不走。
yanqi liu
yanqi liu el 22 de Mzo. de 2022
是的,如果是做分类,则一般fullyconnectedlayer全连接后就要进入classify了,卷积层一般在中间

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