This question refers to the YOLO architecture (figure 3).
In their architecture they define a convolutional layer
7x7x64-s-2 followed by a maxpool layer
2x2-s-2. These transform an input of
448x448x3 into a tensor of
112x112x192, using a kernel of
7x7 in the convolutional layer.
Can someone please clarify this notation
s-2 refers to stride of 2. Then is 64 the padding?