In the SSD model presented in the paper, it is said that the base network is considered as VGG16 and the extra feature layers are added at the end of it that allows feature maps to be produced at different scales and aspect ratios.
My question is that in the architecture shown in Fig.2 (shown below) in the SSD paper, the convolution layers have notations shown like Conv5_3 , Conv4_3, for the base network Conv8_2, Conv9_2, Conv10_2 for the added features layers.
What does this _2, _3 notation means in this?
I have seen the same notations being used in the SSD model description page, where base network VGG16 change to ResNET50 and used notations like Conv5_x, Conv4_x.
What does this _x means for the convolution layer notation?
