# A Deep Learning Approach to Semantic Segmentation of Steel Microstructures
## 5 Conclusions
\begin{table}
\begin{tabular}{r l l l r r r r r} \hline  & **Name** & **Type** & **Activations** & & & & & **Learables** \\ \hline
97 & block\_11\_expand\_BN & Batch Normalization & 14 & 14 & 576 & 1 & SSCB & 1152 \\
98 & block\_11\_expand\_relu & Clipped ReLU & 14 & 14 & 576 & 1 & SSCB & 0 \\
99 & block\_11\_depthwise & 2-D Grouped Convolution & 14 & 14 & 576 & 1 & SSCB & 5760 \\
100 & block\_11\_depthwise\_BN & Batch Normalization & 14 & 14 & 576 & 1 & SSCB & 1152 \\
101 & block\_11\_depthwise\_relu & Clipped ReLU & 14 & 14 & 576 & 1 & SSCB & 0 \\
102 & block\_11\_project & 2-D Convolution & 14 & 14 & 96 & 1 & SSCB & 55,392 \\
103 & block\_11\_project\_BN & Batch Normalization & 14 & 14 & 96 & 1 & SSCB & 192 \\
104 & block\_11\_add & Addition & 14 & 14 & 96 & 1 & SSCB & 0 \\
105 & block\_12\_expand & 2-D Convolution & 14 & 14 & 576 & 1 & SSCB & 55,872 \\
106 & block\_12\_expand\_BN & Batch Normalization & 14 & 14 & 576 & 1 & SSCB & 0 \\
107 & block\_12\_expand\_relu & Clipped ReLU & 14 & 14 & 576 & 1 & SSCB & 5760 \\
108 & block\_12\_depthwise\_BN & Batch Normalization & 14 & 14 & 576 & 1 & SSCB & 5760 \\
110 & block\_12\_depthwise\_relu & Clipped ReLU & 14 & 14 & 576 & 1 & SSCB & 1152 \\
111 & block\_12\_project & 2-D Convolution & 14 & 14 & 96 & 1 & SSCB & 55,392 \\
112 & block\_12\_project\_BN & Batch Normalization & 14 & 14 & 96 & 1 & SSCB & 192 \\
113 & block\_12\_add & Addition & 14 & 14 & 96 & 1 & SSCB & 0 \\
114 & block\_13\_expand & 2-D Convolution & 14 & 14 & 576 & 1 & SSCB & 55,872 \\
115 & block\_13\_expand\_BN & Batch Normalization & 14 & 14 & 576 & 1 & SSCB & 1152 \\
116 & block\_13\_expand\_relu & Clipped ReLU & 14 & 14 & 576 & 1 & SSCB & 0 \\
117 & block\_13\_depthwise\_2 & 2-D Grouped Convolution & 14 & 14 & 576 & 1 & SSCB & 5760 \\
118 & block\_13\_depthwise\_BN & Batch Normalization & 14 & 14 & 576 & 1 & SSCB & 1152 \\
119 & block\_13\_depthwise\_relu & Clipped ReLU & 14 & 14 & 576 & 1 & SSCB & 0 \\
120 & block\_13\_project & 2-D Convolution & 14 & 14 & 160 & 1 & SSCB & 92,320 \\
121 & block\_13\_project\_BN & Batch Normalization & 14 & 14 & 160 & 1 & SSCB & 320 \\
122 & block\_14\_expand & 2-D Convolution & 14 & 14 & 960 & 1 & SSCB & 154,560 \\
123 & block\_14\_expand\_BN & Batch Normalization & 14 & 14 & 960 & 1 & SSCB & 1920 \\
124 & block\_14\_expand\_relu & Clipped ReLU & 14 & 14 & 960 & 1 & SSCB & 0 \\
125 & block\_14\_depthwise & 2-D Grouped Convolution & 14 & 14 & 960 & 1 & SSCB & 9600 \\
126 & block\_14\_depthwise\_BN & Batch Normalization & 14 & 14 & 960 & 1 & SSCB & 1920 \\
127 & block\_14\_depthwise\_relu & Clipped ReLU & 14 & 14 & 960 & 1 & SSCB & 0 \\
128 & block\_14\_project & 2-D Convolution & 14 & 14 & 160 & 1 & SSCB & 153,760 \\
129 & block\_14\_project\_BN & Batch Normalization & 14 & 14 & 160 & 1 & SSCB & 320 \\
130 & block\_14\_add & Addition & 14 & 14 & 160 & 1 & SSCB & 0 \\
131 & block\_15\_expand\_2 & 2-D Convolution & 14 & 14 & 960 & 1 & SSCB & 1920 \\
132 & block\_15\_expand\_BN & Batch Normalization & 14 & 14 & 960 & 1 & SSCB & 0 \\
133 & block\_15\_expand\_relu & Clipped ReLU & 14 & 14 & 960 & 1 & SSCB & 0 \\
134 & block\_15\_depthwise\_2 & 2-D Grouped Convolution & 14 & 14 & 960 & 1 & SSCB & 9600 \\
135 & block\_15\_depthwise\_BN & Batch Normalization & 14 & 14 & 960 & 1 & SSCB & 1920 \\
136 & block\_15\_depthwise\_relu & Clipped ReLU & 14 & 14 & 960 & 1 & SSCB & 0 \\
137 & block\_15\_project & 2-D Convolution & 14 & 14 & 160 & 1 & SSCB & 153,760 \\
138 & block\_15\_project\_BN & Batch Normalization & 14 & 14 & 160 & 1 & SSCB & 320 \\
139 & block\_15\_add & Addition & 14 & 14 & 160 & 1 & SSCB & 0 \\
140 & block\_16\_expand & 2-D Convolution & 14 & 14 & 960 & 1 & SSCB & 154,560 \\
141 & block\_16\_expand\_BN & Batch Normalization & 14 & 14 & 960 & 1 & SSCB & 1920 \\
142 & block\_16\_expand\_relu & Clipped ReLU & 14 & 14 & 960 & 1 & SSCB & 0 \\
143 & block\_16\_depthwise\_2 & 2-D Grouped Convolution & 14 & 14 & 960 & 1 & SSCB & 9600 \\
143 & block\_16\_depthwise\_BN & Batch Normalization & 14 & 14 & 960 & 1 & SSCB & 1920 \\
144 & block\_16\_depthwise\_BN & Batch Normalization & 14 & 14 & 960 & 1 & SSCB & 1920 \\
145 & block\_16\_depthwise\_relu & Clipped ReLU & 14 & 14 & 960 & 1 & SSCB & 0 \\
146 & block\_16\_project & 2-D Convolution & 14 & 14 & 320 & 1 & SSCB & 307,520 \\
147 & block\_16\_project\_BN & Batch Normalization & 14 & 14 & 320 & 1 & SSCB & 640 \\
148 & aspp\_Conv\_1\_depthwise & 2-D Grouped Convolution & 14 & 14 & 320 & 1 & SSCB & 640 \\
149 & aspp\_Conv\_1\_pointwise & 2-D Convolution & 14 & 14 & 256 & 1 & SSCB & 82,176 \\
150 & aspp\_BatchNorm\_1 & Batch Normalization & 14 & 14 & 256 & 1 & SSCB & 512 \\
151 & aspp\_BatchNorm\_1 & ReLU & 14 & 14 & 256 & 1 & SSCB & 0 \\
152 & aspp\_Conv\_2\_depthwise & 2-D Grouped Convolution & 14 & 14 & 320 & 1 & SSCB & 3200 \\
153 & aspp\_Conv\_2\_pointwise & 2-D Grouped Convolution & 14 & 14 & 256 & 1 & SSCB & 82,176 \\
154 & aspp\_BatchNorm\_2 & Batch Normalization & 14 & 14 & 256 & 1 & SSCB & 82,176 \\
155 & aspp\_Conv\_3\_depthwise & 2-D Grouped Convolution & 14 & 14 & 256 & 1 & SSCB & 82,176 \\
156 & aspp\_BatchNorm\_3 & Batch Normalization & 14 & 14 & 256 & 1 & SSCB & 0 \\
157 & aspp\_Conv\_3\_pointwise & 2-D Convolution & 14 & 14 & 256 & 1 & SSCB & 512 \\
158 & aspp\_BatchNorm\_3 & Batch Normalization & 14 & 14 & 256 & 1 & SSCB & 0 \\
159 & aspp\_Rel\_3 & Batch Normalization & 14 & 14 & 320 & 1 & SSCB & 3200 \\
160 & aspp\_Conv\_4\_pointwise & 2-D Convolution & 14 & 14 & 256 & 1 & SSCB & 82,176 \\
162 & aspp\_BatchNorm\_4 & Batch Normalization & 14 & 14 & 256 & 1 & SSCB & 82