Max Pooling Layer Tuning
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Hello,
I'm currently working on implementing a CNN for a regression problem, and I've encountered an issue when using the maxPooling2dLayer with a poolSize greater than 1. Here's the relevant part of my code:
Layers = [imageInputLayer([NIV 1 1])
convolution2dLayer(5, 15, 'Padding', 'same')
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2) % (poolSize > 1 leads to an error!!!)
reluLayer
dropoutLayer(0.5)
fullyConnectedLayer(1)
regressionLayer];
The problem arises when I try to set the poolSize in the maxPooling2dLayer to a value greater than 1. I receive the following errors:
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Error using trainNetwork (line 183)
Invalid network.
Error in CNN (line 280)
net = trainNetwork(XTrain, YTrain, Layers, Options);
Caused by:
Layer 5: Input size mismatch. Size of input to this layer is different from the expected input size.
Inputs to this layer:
from layer 4 (output size 6×1×15)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
I'm seeking assistance to resolve this issue. Any guidance or suggestions you could provide would be greatly appreciated.
Thank you!
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Akzeptierte Antwort
Matt J
am 1 Sep. 2023
Your input image's spatial dimensions are 6x1. This is not compatible with a 2x2 maxpooling filter. Did you mean to have 2x1 pooling instead? If so,
maxPooling2dLayer([2,1])
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