Animation from here . I wonder why the advanced convolution maintains resolution, it is claimed. The blue input appears to be 7x7 and green is 3x3.
EDIT:
One way to get around the loss of resolution is to insert an input with approximately half the size of the current susceptible field, but
5x5. 3x3, 0, .
, , :
. .
. , , 3 3x , 15x15 .
3x3 , 3 (4 ) ( , , , ). 4 3x3 3 3, 15x15.
, , , .
Source: https://habr.com/ru/post/1663921/More articles:Как сохранить уникальность, основанную на конкретном массиве fieldin Без использования уникального индекса - mongodbКакое использование расширенных сверток? - deep-learningGeneration of a generic into a common - castingHow to use the convolution function "tf.nn.atrous_conv2d" in a tensor stream? - tensorflowNodeJS / Jenkins / GIT and Jenkins Slave as a web server - gitразница между кодировкой /gob и кодировкой /json в golang - jsonWhy __call is called instead of __callStatic - phpКак развязать интерфейс {} с интерфейсом {} в Go - jsonHow spring serves a singleton bean to multiple requests at the same time - javaIs / gob encoding deterministic? - goAll Articles