how to calculate quadratic features in computer vision Neural Network
$begingroup$
I am recently watching some tutorials for deep learning from Dr Andrew Ng on Youtube. Link is hereThe Youtube video
There is a concept of number of features in convolutional neural network in TensorFlow's tutorial https://www.tensorflow.org/get_started/mnist/pros#convolution_and_pooling.
I don't quite understand why the feature is 32 or 64 here in conv layer1 or layer2?
Then I came to the video(https://youtu.be/1ZhtwInuOD0?t=9m8s), there is also the concept of Quadratic features. It is calculated as 3 million however. But how is it calculated?
Are the two features related in concept?
neural-network deep-learning tensorflow convolution
asked Aug 14 '17 at 8:27
cinqScinqS
207210
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bumped to the homepage by Community♦ 18 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I am recently watching some tutorials for deep learning from Dr Andrew Ng on Youtube. Link is hereThe Youtube video
There is a concept of number of features in convolutional neural network in TensorFlow's tutorial https://www.tensorflow.org/get_started/mnist/pros#convolution_and_pooling.
I don't quite understand why the feature is 32 or 64 here in conv layer1 or layer2?
Then I came to the video(https://youtu.be/1ZhtwInuOD0?t=9m8s), there is also the concept of Quadratic features. It is calculated as 3 million however. But how is it calculated?
Are the two features related in concept?
neural-network deep-learning tensorflow convolution
asked Aug 14 '17 at 8:27
cinqScinqS
207210
$endgroup$
bumped to the homepage by Community♦ 18 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
$begingroup$
it's common to use powers of two for sizing filters or dense layers in neural networks
$endgroup$
– Vadim Smolyakov
Aug 15 '17 at 18:26
add a comment |
$begingroup$
I am recently watching some tutorials for deep learning from Dr Andrew Ng on Youtube. Link is hereThe Youtube video
There is a concept of number of features in convolutional neural network in TensorFlow's tutorial https://www.tensorflow.org/get_started/mnist/pros#convolution_and_pooling.
I don't quite understand why the feature is 32 or 64 here in conv layer1 or layer2?
Then I came to the video(https://youtu.be/1ZhtwInuOD0?t=9m8s), there is also the concept of Quadratic features. It is calculated as 3 million however. But how is it calculated?
Are the two features related in concept?
neural-network deep-learning tensorflow convolution
asked Aug 14 '17 at 8:27
cinqScinqS
207210
$endgroup$
I am recently watching some tutorials for deep learning from Dr Andrew Ng on Youtube. Link is hereThe Youtube video
There is a concept of number of features in convolutional neural network in TensorFlow's tutorial https://www.tensorflow.org/get_started/mnist/pros#convolution_and_pooling.
I don't quite understand why the feature is 32 or 64 here in conv layer1 or layer2?
Then I came to the video(https://youtu.be/1ZhtwInuOD0?t=9m8s), there is also the concept of Quadratic features. It is calculated as 3 million however. But how is it calculated?
Are the two features related in concept?
neural-network deep-learning tensorflow convolution
neural-network deep-learning tensorflow convolution
asked Aug 14 '17 at 8:27
cinqScinqS
207210
asked Aug 14 '17 at 8:27
cinqScinqS
207210
edited Aug 14 '17 at 8:43
cinqS
asked Aug 14 '17 at 8:27
cinqScinqS
207210
asked Aug 14 '17 at 8:27
cinqScinqS
207210
asked Aug 14 '17 at 8:27
cinqScinqS
207210
207210
bumped to the homepage by Community♦ 18 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 18 hours ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
$begingroup$
it's common to use powers of two for sizing filters or dense layers in neural networks
$endgroup$
– Vadim Smolyakov
Aug 15 '17 at 18:26
add a comment |
$begingroup$
it's common to use powers of two for sizing filters or dense layers in neural networks
$endgroup$
– Vadim Smolyakov
Aug 15 '17 at 18:26
$begingroup$
it's common to use powers of two for sizing filters or dense layers in neural networks
$endgroup$
– Vadim Smolyakov
Aug 15 '17 at 18:26
$begingroup$
it's common to use powers of two for sizing filters or dense layers in neural networks
$endgroup$
– Vadim Smolyakov
Aug 15 '17 at 18:26
add a comment |
1 Answer
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$begingroup$
Sorry for being so late in the response. I have just read your message.
The instructor is using $frac{x^2}2$. So $frac{2500times 2500}2$, and this will get approx $3$ millions features.
BR
edited Jan 10 at 6:39
Siong Thye Goh
1,077418
answered Jan 9 at 16:39
theyoungluketheyoungluke
1
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$begingroup$
Sorry for being so late in the response. I have just read your message.
The instructor is using $frac{x^2}2$. So $frac{2500times 2500}2$, and this will get approx $3$ millions features.
BR
edited Jan 10 at 6:39
Siong Thye Goh
1,077418
answered Jan 9 at 16:39
theyoungluketheyoungluke
1
$endgroup$
add a comment |
$begingroup$
Sorry for being so late in the response. I have just read your message.
The instructor is using $frac{x^2}2$. So $frac{2500times 2500}2$, and this will get approx $3$ millions features.
BR
edited Jan 10 at 6:39
Siong Thye Goh
1,077418
answered Jan 9 at 16:39
theyoungluketheyoungluke
1
$endgroup$
add a comment |
$begingroup$
Sorry for being so late in the response. I have just read your message.
The instructor is using $frac{x^2}2$. So $frac{2500times 2500}2$, and this will get approx $3$ millions features.
BR
edited Jan 10 at 6:39
Siong Thye Goh
1,077418
answered Jan 9 at 16:39
theyoungluketheyoungluke
1
$endgroup$
Sorry for being so late in the response. I have just read your message.
The instructor is using $frac{x^2}2$. So $frac{2500times 2500}2$, and this will get approx $3$ millions features.
BR
edited Jan 10 at 6:39
Siong Thye Goh
1,077418
answered Jan 9 at 16:39
theyoungluketheyoungluke
1
edited Jan 10 at 6:39
Siong Thye Goh
1,077418
edited Jan 10 at 6:39
Siong Thye Goh
1,077418
edited Jan 10 at 6:39
Siong Thye Goh
1,077418
1,077418
answered Jan 9 at 16:39
theyoungluketheyoungluke
1
answered Jan 9 at 16:39
theyoungluketheyoungluke
1
answered Jan 9 at 16:39
theyoungluketheyoungluke
1
1
add a comment |
add a comment |
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$begingroup$
it's common to use powers of two for sizing filters or dense layers in neural networks
$endgroup$
– Vadim Smolyakov
Aug 15 '17 at 18:26