CNN strategy in recognizing spinned images
$begingroup$
I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels change very little during training. Why?
When there are over 10 convolution kernels, my CNN starts to recognize fipped images. So more kernels help.
How will the resolution of images affect the result compared to the convolution kernel size? The higher the resolution, the higher the dimension of this fitting problem
cnn image-recognition kernel
asked 26 mins ago
feynmanfeynman
1578
$endgroup$
add a comment |
$begingroup$
I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels change very little during training. Why?
When there are over 10 convolution kernels, my CNN starts to recognize fipped images. So more kernels help.
How will the resolution of images affect the result compared to the convolution kernel size? The higher the resolution, the higher the dimension of this fitting problem
cnn image-recognition kernel
asked 26 mins ago
feynmanfeynman
1578
$endgroup$
add a comment |
$begingroup$
I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels change very little during training. Why?
When there are over 10 convolution kernels, my CNN starts to recognize fipped images. So more kernels help.
How will the resolution of images affect the result compared to the convolution kernel size? The higher the resolution, the higher the dimension of this fitting problem
cnn image-recognition kernel
asked 26 mins ago
feynmanfeynman
1578
$endgroup$
I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels change very little during training. Why?
When there are over 10 convolution kernels, my CNN starts to recognize fipped images. So more kernels help.
How will the resolution of images affect the result compared to the convolution kernel size? The higher the resolution, the higher the dimension of this fitting problem
cnn image-recognition kernel
cnn image-recognition kernel
asked 26 mins ago
feynmanfeynman
1578
asked 26 mins ago
feynmanfeynman
1578
edited 45 secs ago
feynman
asked 26 mins ago
feynmanfeynman
1578
asked 26 mins ago
feynmanfeynman
1578
asked 26 mins ago
feynmanfeynman
1578
1578
add a comment |
add a comment |
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