Freaks City

Convolutional operations reduce spatial dimensions when processing inputs. For an input tensor of size \(n_h \times n_w\) and kernel dimensions \(k_h \times k_w\), output dimentions become \((n_h-k_h+1) \times (n_w-k_w+1)\). Sequential convolutions exacerbate this reduction - a \(240 \times 240\) image processed through ten \(5\times5\) convolu ...