A convolutional layer has produced a block of two feature maps — a block.
Map 1
| col 0 | col 1 | col 2 | col 3 | |
|---|---|---|---|---|
| row 0 | 1 | 8 | 3 | 2 |
| row 1 | 4 | 2 | 9 | 1 |
| row 2 | 7 | 0 | 5 | 12 |
| row 3 | 6 | 3 | 2 | 4 |
Map 2
| col 0 | col 1 | col 2 | col 3 | |
|---|---|---|---|---|
| row 0 | 5 | 1 | 0 | 6 |
| row 1 | 2 | 3 | 4 | 4 |
| row 2 | 9 | 8 | 1 | 1 |
| row 3 | 7 | 2 | 3 | 0 |
The same block is sent, unchanged, into two different pooling layers:
Add up every number that comes out of layer M, and add up every number that comes out of layer A.
What is (layer M total) (layer A total)?
Round your answer to 2 decimal places.