modify
lgraph = replaceLayer(lgraph,'fc6',newFCLayer);
to
lgraph = replaceLayer(lgraph,'fc8',newFCLayer);
net = alexnet;
net.Layers
ans =
25×1 Layer array with layers:
1 'data' Image Input 227×227×3 images with 'zerocenter' normalization
2 'conv1' Convolution 96 11×11×3 convolutions with stride [4 4] and padding [0 0 0 0]
3 'relu1' ReLU ReLU
4 'norm1' Cross Channel Normalization cross channel normalization with 5 channels per element
5 'pool1' Max Pooling 3×3 max pooling with stride [2 2] and padding [0 0 0 0]
6 'conv2' Grouped Convolution 2 groups of 128 5×5×48 convolutions with stride [1 1] and padding [2 2 2 2]
7 'relu2' ReLU ReLU
8 'norm2' Cross Channel Normalization cross channel normalization with 5 channels per element
9 'pool2' Max Pooling 3×3 max pooling with stride [2 2] and padding [0 0 0 0]
10 'conv3' Convolution 384 3×3×256 convolutions with stride [1 1] and padding [1 1 1 1]
11 'relu3' ReLU ReLU
12 'conv4' Grouped Convolution 2 groups of 192 3×3×192 convolutions with stride [1 1] and padding [1 1 1 1]
13 'relu4' ReLU ReLU
14 'conv5' Grouped Convolution 2 groups of 128 3×3×192 convolutions with stride [1 1] and padding [1 1 1 1]
15 'relu5' ReLU ReLU
16 'pool5' Max Pooling 3×3 max pooling with stride [2 2] and padding [0 0 0 0]
17 'fc6' Fully Connected 4096 fully connected layer
18 'relu6' ReLU ReLU
19 'drop6' Dropout 50% dropout
20 'fc7' Fully Connected 4096 fully connected layer
21 'relu7' ReLU ReLU
22 'drop7' Dropout 50% dropout
23 'fc8' Fully Connected 1000 fully connected layer
24 'prob' Softmax softmax
25 'output' Classification Output crossentropyex with 'tench' and 999 other classes
