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I was reading your paper -
. Then, each image was randomly scaled both vertically and horizontally in the range of [0.5, 1]. Each colour channel was randomly shifted within the range of ±25 (i.e. approximately ±10% of the maximum available 8-bit colour encoding range [0, 255]). To account for illumination variance, pixel intensity was randomly shifted within the [−25, +25] range, shifting all colour channels uniformly. In addition, pixel intensity was randomly scaled within the [0.75, 1.25] range
Are you familiar with this repo https://github.com/tueimage/SE2CNN ?
It may be more fruitful in optimizing network by automagically providing roto scale invariance.
The text was updated successfully, but these errors were encountered:
I was reading your paper -
. Then, each image was randomly scaled both vertically and horizontally in the range of [0.5, 1]. Each colour channel was randomly shifted within the range of ±25 (i.e. approximately ±10% of the maximum available 8-bit colour encoding range [0, 255]). To account for illumination variance, pixel intensity was randomly shifted within the [−25, +25] range, shifting all colour channels uniformly. In addition, pixel intensity was randomly scaled within the [0.75, 1.25] range
Are you familiar with this repo https://github.com/tueimage/SE2CNN ?
It may be more fruitful in optimizing network by automagically providing roto scale invariance.
The text was updated successfully, but these errors were encountered: