# FSRFNet: Feature-selective and Spatial Receptive Fields Networks
## 5 Experiments
### Tiny ImageNet Classification  
Tiny ImageNet [54] has 200 classes. Each class has 500 training images, 50 validation images, and 50 test images. We train the network on the training set and report the top-1 errors on the validation set. For data enhancement, we follow standard practices and perform random size cropping to \(224\times 224\) and random horizontal flipping [2]. We use synchronous SGD with a momentum of 0.9, a mini-batch size of 32, and a weight decay of \(1\times 10^{-4}\). The initial learning rate is set to 0.5 and decreased by a factor of 10 every 30 epochs. All models are trained for 100 epochs from scratch on one GPU, using the weight initialization strategy in [55]. We first compare FSRFNet-50 and FSRFNet-101 with a publicly competitive model of similar complexity. The results show that the FSRF block is consistent in improving the performance of state-of-the-art attention-based CNNs. We begin by comparing FSRFNets to the public competitive models with different depths. Table 2 and Figure 5 show the comparison results on the Tiny ImageNet [54] validation set. As the illustrations show, FSRFNet-50 and FSRFNet-101 improve the performance of state-of-the-art attention-based network models at different depths compared to models of similar complexity. FSRFNet-50 and FSRFNet-101 achieve performance improvements of 5.1% and 5.5% over ResNeXt-50 and ResNeXt-101, respectively. In addition, FSRFNet-50 and FSRFNet-101 achieve performance increases of 2.9% and 3.7% compared to SENet-50 and SENet-101, respectively. We note also that gains of 1.5% and 1.7% can be obtained for FSRFNet-50 and FSRFNet-101, compared to SKNet-50 and SKNet-101, respectively. Surprisingly, FSRFNet-50 is not only 1.27% higher than the absolute accuracy of ResNeXt-101, but the  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Output** & **ResNeXt-50 02\(\times\)40** & **SENet-50** & **SENet-50** & **FSRFNet-50** \\ \hline \(112\times 112\) & & & conv, \(7\times 7\), 64, stride 2 & \\ \(112\times 112\) & & & max pool, \(3\times 3\), stride 2 & \\ \(56\times 56\) & \(\left[ \begin{array}{c}1\times 1,128\\ 3\times 3,128,G-32\\ 1\times 1,256\end{array} \right]\times 3\) & \(\left[ \begin{array}{c}1\times 1,128\\ 3\times 3,128,G-32\\ 1\times 1,256\end{array} \right]\times 3\) & \(\left[ \begin{array}{c}1\times 1,128\\ 3\times 3,128,G-32\\ 1\times 1,256\end{array} \right]\times 3\) & \(\left[ \begin{array}{c}1\times 1,128\\ 3\times 3,128,G-32\\ 1\times 1,256\end{array} \right]\times 3\) & \(\left[ \begin{array}{c}1\times 1,128\\ 1\times 1,28\\ 1\times 1,286\end{array} \right]\times 3\) & \(\left[ \begin{array}{c}1\times 1,128\\ 3\times 3,128,G-32\\ 1\times 1,256\end{array} \right]\times 128\) & \(\times 3\) & \(\left[ \begin{array}{c}1\times 1,128\\ 3\times 3,128,G-32\\ 1\times 1,256\end{array} \right]\times 128\) & \(\times 3\) \\ \(28\times 28\) & \(\left[ \begin{array}{c}1\times 1,256\\ 3\times 3,266,G-32\\ 1\times 1,512\end{array} \right]\times 4\) & \(\left[ \begin{array}{c}1\times 1,256\\ 3\times 3,256,G-32\\ 1\times 1,512\end{array} \right]\times 4\) & \(\left[ \begin{array}{c}1\times 1,256\\ 3\times 3,256,G-32\\ 1\times 1,512\end{array} \right]\times 4\) & \(\left[ \begin{array}{c}1\times 1,256\\ 3\times 3,256,G-32\\ 1\times 1,512\end{array} \right]\times 26\) & \(\left[ \begin{array}{c}1\times 1,126\\ 3\times 1,512\\ 4\end{array} \right]\times 128\) & \(\left[ \begin{array}{c}1\times 1,128\\ 1\times 1,512\\ 4\end{array} \right]\times 128\) \\ \(14\times 14\) & \(\left[ \begin{array}{c}1\times 1,512\\ 3\times 3,512,G-32\\ 1\times 1,1024\end{array} \right]\times 6\) & \(\left[ \begin{array}{c}1\times 1,512\\ 3\times 3,512,G-32\\ 1\times 1,1024\end{array} \right]\times 6\) & \(\left[ \begin{array}{c}1\times 1,512\\ 3\times 3,124,G-32\\ 1\times 1,2048\end{array} \right]\times 3\) & \(\left[ \begin{array}{c}1\times 1,124\\ 3\times 3,124,G-32\\ 1\times 1,2048\end{array} \right]\times 3\) & \(\left[ \begin{array}{c}1\times 1,124\\ 3\times 3,124,G-32\\ 1\times 1,2048\end{array} \right]\times 3\) & \(\left[