Table 1.

The structures of the ResNets: ResNet50, ResNet98, and ResNet101 represent that the number of layers is 50, 98, and 101, respectively.

Layer	Output Size	ResNet50	ResNet101	ResNet98
Conv_1	$112\times 112$	$\left[\begin{array}{cc}7\times 7& 64\end{array}\right]$
Conv_2	$28\times 28$	$\left[\begin{array}{cc}1\times 1& 64\\ 3\times 3& 64\\ 1\times 1& 256\end{array}\right]\times 3$	$\left[\begin{array}{cc}1\times 1& 64\\ 3\times 3& 64\\ 1\times 1& 256\end{array}\right]\times 3$	$\left[\begin{array}{cc}1\times 1& 64\\ 3\times 3& 64\\ 1\times 1& 256\end{array}\right]\times 3$
Conv_3	$14\times 14$	$\left[\begin{array}{cc}1\times 1& 128\\ 3\times 3& 128\\ 1\times 1& 512\end{array}\right]\times 4$	$\left[\begin{array}{cc}1\times 1& 128\\ 3\times 3& 128\\ 1\times 1& 512\end{array}\right]\times 4$	$\left[\begin{array}{cc}1\times 1& 128\\ 3\times 3& 128\\ 1\times 1& 512\end{array}\right]\times 3$
Conv_4	$7\times 7$	$\left[\begin{array}{cc}1\times 1& 256\\ 3\times 3& 256\\ 1\times 1& 1024\end{array}\right]\times 6$	$\left[\begin{array}{cc}1\times 1& 256\\ 3\times 3& 256\\ 1\times 1& 1024\end{array}\right]\times 23$	$\left[\begin{array}{cc}1\times 1& 256\\ 3\times 3& 256\\ 1\times 1& 1024\end{array}\right]\times 22$
Conv_5	$7\times 7$	$\left[\begin{array}{cc}1\times 1& 512\\ 3\times 3& 512\\ 1\times 1& 2048\end{array}\right]\times 3$	$\left[\begin{array}{cc}1\times 1& 512\\ 3\times 3& 512\\ 1\times 1& 2048\end{array}\right]\times 3$	$\left[\begin{array}{cc}1\times 1& 512\\ 3\times 3& 512\\ 1\times 1& 2048\end{array}\right]\times 3$
Average Pooling	$1\times 1$	1000 dimensions