有人可以解释如何在 caffe 中使用 Conv3d 和 ConvND 吗?
Can someone explain how to use Conv3d and ConvND in caffe?
有人可以解释一下如何将 Conv3D
或 ConvND
用于 Depth-images
或视频或 [=13= 中的几乎任何 3d(n-d?)数据] ?
Conv3D 是否有任何示例或演示?
您可以使用常规 "Convolution"
层来处理任何维度的斑点。你只需要密切关注参数:
layer {
type: "Convolution"
name: "conv_nd"
bottom: "in" # 5D blob
too: "out"
convolution_param {
kernel_size: 3
kernel_size: 5
kernel_size: 5 # define 3 by 5 by 5 kernel
pad: 1
pad: 2
pad: 2 # pad according to kernel size
stride: 1
stride: 2
stride: 2 # you can have different stride for different dimensions
axis: 1 # the "channel" dimension
num_output: 30 # output 30 dim per 3D voxel
}
}
有关更多信息,请阅读 caffe.proto file 中关于卷积参数的注释。
有人可以解释一下如何将 Conv3D
或 ConvND
用于 Depth-images
或视频或 [=13= 中的几乎任何 3d(n-d?)数据] ?
Conv3D 是否有任何示例或演示?
您可以使用常规 "Convolution"
层来处理任何维度的斑点。你只需要密切关注参数:
layer {
type: "Convolution"
name: "conv_nd"
bottom: "in" # 5D blob
too: "out"
convolution_param {
kernel_size: 3
kernel_size: 5
kernel_size: 5 # define 3 by 5 by 5 kernel
pad: 1
pad: 2
pad: 2 # pad according to kernel size
stride: 1
stride: 2
stride: 2 # you can have different stride for different dimensions
axis: 1 # the "channel" dimension
num_output: 30 # output 30 dim per 3D voxel
}
}
有关更多信息,请阅读 caffe.proto file 中关于卷积参数的注释。