My image size is of [566 804 3], what are the useful convolution filter sizes? How can I predict them? Every where I just given the same filter size and same number of filters?

1 次查看(过去 30 天)
layers=[...
imageInputLayer([566 804 3])
convolution2dLayer(50, 20)
reluLayer
crossChannelNormalizationLayer(2)
maxPooling2dLayer(5,'stride',2,'padding',2)
convolution2dLayer(50, 20)
reluLayer
crossChannelNormalizationLayer(2)
maxPooling2dLayer(5,'stride',2,'padding',2)
convolution2dLayer(50, 20)
reluLayer
crossChannelNormalizationLayer(2)
maxPooling2dLayer(5,'stride',2,'padding',2)
convolution2dLayer(50, 20)
reluLayer
convolution2dLayer(50, 20)
reluLayer
convolution2dLayer(50, 20)
reluLayer
maxPooling2dLayer(5,'stride',2,'padding',2)
fullyConnectedLayer(2)
softmaxLayer
classificationLayer()]

回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Image Data Workflows 的更多信息

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by