Convolutional Layer
/ˌkɒnvəˈluːʃənəl ˈleɪər/
A layer in CNNs that applies convolution operations to extract spatial features from input data.
In italiano: Layer ConvoluzionaleConvolutional layers use learnable filters (kernels) that slide over input to detect local patterns. Multiple filters detect different features like edges, textures, or shapes. Output is a feature map.
Examples
- Edge detection in images
- Pattern recognition
- Feature extraction in CNNs