I'm trying to implement the CNN algorithm that used on paper (A Deep-Network Solution Towards Model-less Obstacle Avoidance)for Lei Tai, Shaohua Li, and Ming Liu; and when I put their specification of CNN layers; I got the following error: using nnet.cnn.layer.Layer>iInferSize (line 266) Layer 5 is expected to have a different size. if anyone has an idea what is going on, which size they mean? and why I got this error? plese, let me Know.
layers = [imageInputLayer([120 160 1],'Normalization','none'); convolution2dLayer(5,32,'NumChannels',1); reluLayer(); maxPooling2dLayer(2,'Stride',2); convolution2dLayer(5,32,'NumChannels',1); reluLayer(); maxPooling2dLayer(2,'Stride',2); convolution2dLayer(5,64) reluLayer(); maxPooling2dLayer(2,'Stride',2); fullyConnectedLayer(5); softmaxLayer classificationLayer()];
The error is located in the "NumChannels", it must have the same amout of channels of the filters used in the poir Convolution layer, so, the correct way to write it is:
convolution2dLayer(5,32,'NumChannels',1); reluLayer(); maxPooling2dLayer(2,'Stride',2); convolution2dLayer(5,32,'NumChannels', 32); reluLayer(); maxPooling2dLayer(2,'Stride',2); convolution2dLayer(5,64) reluLayer(); maxPooling2dLayer(2,'Stride',2); fullyConnectedLayer(5); softmaxLayer classificationLayer()];
In other cases, it may be no necessary to specify the number of channels, and let it be automaticaly get.
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