Update index.md

index.md

@@ -15,10 +15,10 @@ In this project, we will build a deep convolutional neural network (CNN) based o
 Aayush Mishra (https://www.kaggle.com/aayushmishra1512/emotion-detector), which consists of five CNN modules. The model contains about 4.5 million parameters. The batch normalization and dropout techniques are used to make the model robust. The detailed structure is shown in Fig.3. 
 
 <p align="center"> <img src="Fig/1.png" alt="hi" class="inline"/> </p>
-<div align="center"> Figure 1. Conventional FER method.<sup>[1]</sup> </div>
+<div align="center"> Figure 1. Conventional FER method.<sup>[1]</sup> </div> <br>
 
 <p align="center"> <img src="Fig/2.png" alt="hi" class="inline"/> </p>
-<div align="center"> Figure 2. Deep neural networks-based FER approach.<sup>[1]</sup> </div>
+<div align="center"> Figure 2. Deep neural networks-based FER approach.<sup>[1]</sup> </div> <br>
 
 <p align="center"> <img src="Fig/3.png" alt="hi" class="inline"/> </p>
 <div align="center"> Figure 3. The architecture of CNN </div> <br>