Name of convolutional layer | Input size | Kernel | Stride | Output size |
---|---|---|---|---|
Conv1_x | 300*300 | 7*7, 64 | 2 | 150*150*64 |
Conv2_x | 150*150*64 | 3*3 max pool | 2 | 75*75*256 |
\(\left[ {\begin{array}{*{20}c} {1*1} & {64} \\ {3*3} & {64} \\ {1*1} & {256} \\ \end{array} } \right]\)*3 | 1 | |||
Conv3_x | 75*75*256 | \(\left[ {\begin{array}{*{20}c} {1*1} & {128} \\ {3*3} & {128} \\ {1*1} & {512} \\ \end{array} } \right]\)*4 | 2 | 38*38*512 |
Conv4_x | 38*38*512 | \(\left[ {\begin{array}{*{20}c} {1*1} & {256} \\ {3*3} & {256} \\ {1*1} & {1024} \\ \end{array} } \right]\)*6 | 1 | 38*38*1024 |