How does matlab perform the image zero-centering in input layer?
Ältere Kommentare anzeigen
I am using the CNN to classify the objects. In input layer matlab itself implements the training data to zero-center by default.
I am wondering how it is performing this zero centering? Is it the per-pixel mean of channel-wise mean for image data? Is it dividing the images by traing data standard deviation?
inputlayer = imageInputLayer(inputSize,Name,Value)
'Normalization' — Data transformation 'zerocenter' (default) | 'none'
Data transformation to apply every time data is forward-propagated through the input layer,
specified as the comma-separated pair consisting of 'Normalization' and one of the following.
'zerocenter' — The software subtracts its mean from the training set.
'none' — No transformation.
Example: 'Normalization','none'
Data Types: char
Antworten (2)
Arnav Mendiratta
am 12 Jun. 2017
1 Stimme
Zerocenter normalization means having the data dimensions of approximately the same scale. This is done by dividing each dimension (channel) by its standard deviation once it has been zero-centered. Zero-centering means subtracting the mean from each of these dimension so that "data cloud" is centered towards the origin.
This answer talks about the motivation behind using this approach for CNN.
1 Kommentar
Jay
am 19 Jun. 2017
Erik Anzalone
am 26 Okt. 2018
0 Stimmen
How can I find the zero centering? How AverageImage is computed?
1 Kommentar
Greg Heath
am 26 Okt. 2018
PLEASE DO NOT PUT QUESTIONS IN THE ANSWER OR COMMENT BOXES!!!
Thank you!
Kategorien
Mehr zu Object Detection finden Sie in Hilfe-Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!