Convolution Forward | CNN | AI | скачать в хорошем качестве

Convolution Forward | CNN | AI |

#ai #datascience In the convolution forward pass, a small filter (kernel) slides over the input image and performs element-wise multiplication with local patches of the image. The results are summed and a bias is added to produce one output value. This process is repeated across the image using stride and padding, generating feature maps that capture important spatial patterns like edges, textures, and shapes. Convolution helps neural networks learn visual features efficiently while reducing the number of parameters.