How to implement an ensemble of CNNs in Caffe?
1
I would like to train an ensemble of CNNs in Caffe.
- What layers do I use to combine the softmax outputs to make decision by averaging? I am thinking perhaps adding a Concat layer followed by Pooling average layer in the TEST phase would do the trick?
- Each CNN should see different region in the image. Do I use several Crop layers to do this i.e. a Crop layer for each network ?
Thanks.
caffe
asked Nov 19 '18 at 7:22
ng0323ng0323
112212
add a comment |
1
I would like to train an ensemble of CNNs in Caffe.
- What layers do I use to combine the softmax outputs to make decision by averaging? I am thinking perhaps adding a Concat layer followed by Pooling average layer in the TEST phase would do the trick?
- Each CNN should see different region in the image. Do I use several Crop layers to do this i.e. a Crop layer for each network ?
Thanks.
caffe
asked Nov 19 '18 at 7:22
ng0323ng0323
112212
do you train each component of the ensemble separately?
– Shai
Nov 19 '18 at 7:37
Ideally, I would like to train them jointly. I imagine that only one prototxt file will do, just different names for the corresponding layers e.g. for the first conv layer: "conv1_cnn1", "conv1_cnn2", "conv1_cnn3"...
– ng0323
Nov 19 '18 at 7:53
but do you expect a single loss for all nets, or a loss per net (during training)?
– Shai
Nov 19 '18 at 7:59
it would be the total loss of all the nets
– ng0323
Nov 19 '18 at 8:08
add a comment |
1
1
1
I would like to train an ensemble of CNNs in Caffe.
- What layers do I use to combine the softmax outputs to make decision by averaging? I am thinking perhaps adding a Concat layer followed by Pooling average layer in the TEST phase would do the trick?
- Each CNN should see different region in the image. Do I use several Crop layers to do this i.e. a Crop layer for each network ?
Thanks.
caffe
asked Nov 19 '18 at 7:22
ng0323ng0323
112212
I would like to train an ensemble of CNNs in Caffe.
- What layers do I use to combine the softmax outputs to make decision by averaging? I am thinking perhaps adding a Concat layer followed by Pooling average layer in the TEST phase would do the trick?
- Each CNN should see different region in the image. Do I use several Crop layers to do this i.e. a Crop layer for each network ?
Thanks.
caffe
caffe
asked Nov 19 '18 at 7:22
ng0323ng0323
112212
asked Nov 19 '18 at 7:22
ng0323ng0323
112212
asked Nov 19 '18 at 7:22
ng0323ng0323
112212
asked Nov 19 '18 at 7:22
ng0323ng0323
112212
asked Nov 19 '18 at 7:22
ng0323ng0323
112212
112212
do you train each component of the ensemble separately?
– Shai
Nov 19 '18 at 7:37
Ideally, I would like to train them jointly. I imagine that only one prototxt file will do, just different names for the corresponding layers e.g. for the first conv layer: "conv1_cnn1", "conv1_cnn2", "conv1_cnn3"...
– ng0323
Nov 19 '18 at 7:53
but do you expect a single loss for all nets, or a loss per net (during training)?
– Shai
Nov 19 '18 at 7:59
it would be the total loss of all the nets
– ng0323
Nov 19 '18 at 8:08
add a comment |
do you train each component of the ensemble separately?
– Shai
Nov 19 '18 at 7:37
Ideally, I would like to train them jointly. I imagine that only one prototxt file will do, just different names for the corresponding layers e.g. for the first conv layer: "conv1_cnn1", "conv1_cnn2", "conv1_cnn3"...
– ng0323
Nov 19 '18 at 7:53
but do you expect a single loss for all nets, or a loss per net (during training)?
– Shai
Nov 19 '18 at 7:59
it would be the total loss of all the nets
– ng0323
Nov 19 '18 at 8:08
do you train each component of the ensemble separately?
– Shai
Nov 19 '18 at 7:37
do you train each component of the ensemble separately?
– Shai
Nov 19 '18 at 7:37
Ideally, I would like to train them jointly. I imagine that only one prototxt file will do, just different names for the corresponding layers e.g. for the first conv layer: "conv1_cnn1", "conv1_cnn2", "conv1_cnn3"...
– ng0323
Nov 19 '18 at 7:53
Ideally, I would like to train them jointly. I imagine that only one prototxt file will do, just different names for the corresponding layers e.g. for the first conv layer: "conv1_cnn1", "conv1_cnn2", "conv1_cnn3"...
– ng0323
Nov 19 '18 at 7:53
but do you expect a single loss for all nets, or a loss per net (during training)?
– Shai
Nov 19 '18 at 7:59
but do you expect a single loss for all nets, or a loss per net (during training)?
– Shai
Nov 19 '18 at 7:59
it would be the total loss of all the nets
– ng0323
Nov 19 '18 at 8:08
it would be the total loss of all the nets
– ng0323
Nov 19 '18 at 8:08
add a comment |
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do you train each component of the ensemble separately?
– Shai
Nov 19 '18 at 7:37
Ideally, I would like to train them jointly. I imagine that only one prototxt file will do, just different names for the corresponding layers e.g. for the first conv layer: "conv1_cnn1", "conv1_cnn2", "conv1_cnn3"...
– ng0323
Nov 19 '18 at 7:53
but do you expect a single loss for all nets, or a loss per net (during training)?
– Shai
Nov 19 '18 at 7:59
it would be the total loss of all the nets
– ng0323
Nov 19 '18 at 8:08