CCNNet: a novel lightweight convolutional neural network and its application in traditional Chinese medicine recognition

Gang, Hu; Guanglei, Sheng; Xiaofeng, Wang; Jinlin, Jiang

doi:10.1186/s40537-023-00795-4

Journal of Big Data

Table 2 The specific structure of the CCNNet

From: CCNNet: a novel lightweight convolutional neural network and its application in traditional Chinese medicine recognition

Outsize	Layer	CCNNet1.0X	CCNNet1.5X	CCNNet2.0X	CCNNet3.0X
\(72 \times 72\)	Stem	\(3 \times 3,128,stride = 3\)\(\left[ {3 \times 3,128} \right] \times 2\)	\(3 \times 3,160,stride = 3\)\(\left[ {3 \times 3,160} \right] \times 2\)	\(3 \times 3,192,stride = 3\)\(\left[ {3 \times 3,192} \right] \times 2\)	\(3 \times 3,256,stride = 3\)\(\left[ {3 \times 3,256} \right] \times 2\)
Stage1	GCIR	\(\left[ {\begin{array}{*{20}c} {3 \times 3,128} \\ {MDCA} \\ {1 \times 1,512} \\ {1 \times 1,128} \\ \end{array} } \right] \times 3\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,160} \\ {MDCA} \\ {1 \times 1,640} \\ {1 \times 1,160} \\ \end{array} } \right] \times 3\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,192} \\ {MDCA} \\ {1 \times 1,768} \\ {1 \times 1,192} \\ \end{array} } \right] \times 3\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,256} \\ {MDCA} \\ {1 \times 1,1024} \\ {1 \times 1,256} \\ \end{array} } \right] \times 3\)
\(24 \times 24\)	DS	\(3 \times 3,64,stride = 3\)	\(3 \times 3,80,stride = 3\)	\(3 \times 3,96,stride = 3\)	\(3 \times 3,128,stride = 3\)
Stage2	GCIR	\(\left[ {\begin{array}{*{20}c} {3 \times 3,64} \\ {MDCA} \\ {1 \times 1,256} \\ {1 \times 1,64} \\ \end{array} } \right] \times 9\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,80} \\ {MDCA} \\ {1 \times 1,320} \\ {1 \times 1,80} \\ \end{array} } \right] \times 9\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,96} \\ {MDCA} \\ {1 \times 1,384} \\ {1 \times 1,96} \\ \end{array} } \right] \times 9\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,128} \\ {MDCA} \\ {1 \times 1,512} \\ {1 \times 1,128} \\ \end{array} } \right] \times 9\)
\(8 \times 8\)	DS	\(3 \times 3,128,stride = 3\)	\(3 \times 3,160,stride = 3\)	\(3 \times 3,192,stride = 3\)	\(3 \times 3,256,stride = 3\)
Stage3	GCIR	\(\left[ {\begin{array}{*{20}c} {3 \times 3,128} \\ {MDCA} \\ {1 \times 1,512} \\ {1 \times 1,128} \\ \end{array} } \right] \times 3\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,160} \\ {MDCA} \\ {1 \times 1,640} \\ {1 \times 1,160} \\ \end{array} } \right] \times 3\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,192} \\ {MDCA} \\ {1 \times 1,768} \\ {1 \times 1,192} \\ \end{array} } \right] \times 3\)	\(\left[ {\begin{array}{*{20}c} {3 \times 3,256} \\ {MDCA} \\ {1 \times 1,1024} \\ {1 \times 1,256} \\ \end{array} } \right] \times 3\)
\(1 \times 1\)	GAP	\(AvgPool(1 \times 1)\)
\(1 \times 1\)	FC	\(1 \times 1,1000\)
Parameter		1.4 M	2.2 M	3.1 M	5.4 M
Flops		0.36B	0.46B	0.55B	0.74B

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