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View Code? Open in Web Editor NEWUnsupervised Spatial-Spectral Feature Learning by 3-Dimensional Convolutional Autoencoder for Hyperspectral Classification
Unsupervised Spatial-Spectral Feature Learning by 3-Dimensional Convolutional Autoencoder for Hyperspectral Classification
When i run train.py, mode = test, I get this error:
ValueError: Layer #2 (named "PReLU1"), weight <tf.Variable 'PReLU1/alpha:0' shape=(201, 143, 143, 24) dtype=float32_ref> has shape (201, 143, 143, 24), but the saved weight has shape (201, 3, 3, 24).
Excuse me, what tool do you use to draw the 3D hyperspectral map in the proposed structure map ? Thank you for your reply !
DCAE_v2:" model.add(Conv3DTranspose(filters=1,
kernel_size=(27, 3, 3),
kernel_regularizer=regularizers.l2(
l=weight_decay),"
in this code,"filters=1" is not matched the parameters of paper"Deconv4 kernel size: 27x3x3x24",the out size should be 27,not 1
Thanks for sharing, how can I check the classification accuracy?
Hi,
Can you please describe how to test the algorithm using test.py as i think the following code testing code does nothing
"model_name = model_name+'_{}.model'.format(epoch)
feature_model = DCAE_fea()
feature_model.load_weights(self.model_name, by_name=True) "
Also, there's is an error
"ImportError: cannot import name 'DCAE_LR'
as there's no function named DCAE_LR in DCAE_v2.py
please explain .... waiting for your reply
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