Error when using convolution2dLayer between connected
Error when using convolution2dLayer between connected maxPooling2dLayer and maxUnpooling2dLayer I'm trying to create a modified UNet using connected max pooling and max unpooling layers. However, if I put a convolution layer between the pooling and unpooling layers, the network isn't valid. The error is reported for the unpooling layer: Input size mismatch. Size of input to this layer is different from the expected input size. The sizes for the CONV layer, MAXPOOL indices, and MAXPOOL size inputs are all different. Minimum working example below. Am I missing something obvious, or is it not possible to use other layers between maxpool and maxunpool? % define layers layers = [ imageInputLayer([128, 128], 'Name', 'INPUTLAYER') maxPooling2dLayer([2 2], 'HasUnpoolingOutputs', true, 'Stride', [2 2], 'Name', 'MAXPOOL') convolution2dLayer([3 3], 32, 'Padding', 'same', 'Stride', [1 1], 'Name', 'CONV') maxUnpooling2dLayer('Name', 'UNPOOL') regressionLayer('Name', 'MSE') ]; % define network lgraph = layerGraph(layers); % define connections lgraph = connectLayers(lgraph, 'MAXPOOL/indices', 'UNPOOL/indices'); lgraph = connectLayers(lgraph, 'MAXPOOL/size', 'UNPOOL/size'); % plot and check analyzeNetwork(lgraph);
John Williams answered .
2025-11-20
% define layers
layers = [
imageInputLayer([128, 128], 'Name', 'INPUTLAYER')
maxPooling2dLayer([2 2], 'HasUnpoolingOutputs', true, 'Stride', [2 2], 'Name', 'MAXPOOL')
convolution2dLayer([3 3], 1, 'Padding', 'same', 'Stride', [1 1], 'Name', 'CONV')
maxUnpooling2dLayer('Name', 'UNPOOL')
regressionLayer('Name', 'MSE')
];
% define network
lgraph = layerGraph(layers);
% define connections
lgraph = connectLayers(lgraph, 'MAXPOOL/indices', 'UNPOOL/indices');
lgraph = connectLayers(lgraph, 'MAXPOOL/size', 'UNPOOL/size');
% plot and check
analyzeNetwork(lgraph);