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Results tagged with cnn
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user 41591
Convolutional Neural Networks (CNN, also called ConvNets) are a tool used for classification tasks and image recognition. The name giving first step is the extraction of features from the input data.
2
votes
2
answers
372
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Understanding the filter function in Convolution Neural Networks
I am trying to follow the following tutorial accessible with this link.
Under the 3rd Heading, "3. Visualize the Activation Maps for Each Filter", we can see the following function:
def apply_filter(i …
- 861
1
vote
1
answer
79
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Isn't the depth of a convolutional layer, the number of colors (or colorspace size)?
I have been going through a CNN tutorial and noticed that depth of a convolutional layer is equal to the number of filters. But, shouldn't the depth be the number of colors in the image? …
- 861
0
votes
1
answer
559
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why this naming convention for padding as "Same" and "Valid" in keras
I was going through CNN's and found that padding argument should be set to "Valid" if i need no padding and "Same" if i need padding. But, it doesn't make any sense to me. Why can't keras development …
- 861
0
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1
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848
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0
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1
answer
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Does Convolution kernel size affect number of channels?
I am going through Dilated Residual Network blog post. In this, Under 2.Multi-scale Context aggregation heading, author mentioned this.
The last one is the 1×1 convolutions for mapping the number …
- 861
0
votes
Accepted
ValueError in CNN+RNN model in keras
the best way to do CNN+LSTM is using Time distributed layer. following code show's how we can add Time Distributed layer
model = Sequential()
model.add(TimeDistributed(Conv2D(24, 5, 5,activation='relu …
- 861
0
votes
2
answers
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ValueError in CNN+RNN model in keras
I am trying to build a CNN+RNN model for a computer vision problem.
below is my code
def cnn_with_rnn(shape):
model = Sequential()
model.add(Conv2D(32, (3, 3), strides=(2, 2), activation="relu … When i am trying to run the above code , i am getting the following error
ValueError: Input 0 is incompatible with layer lstm_3: expected ndim=3, found ndim=4
How can i combine CNN+RNN for colored images …
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