The feature maps at the last convolutional layer, produced by 1 × 1 × 1 1 \times 1 \times 1 1 ×1 × 1 size kernels, represent outputs of the same size as the input volume, and are then converted to ...

Input Layer: The image data is fed into the network as a multi-dimensional array representing pixel values (for example, 32x32x3 for an RGB image). Convolutional Layers: These layers are the heart ...

Pooling Layers Following the convolutional layers, pooling layers perform strategic data reduction, preserving essential information while minimizing computational requirements.